Compare commits
No commits in common. "main" and "important-backup" have entirely different histories.
main
...
important-
@ -1,2 +0,0 @@
|
|||||||
DATABASE_URL=sqlite:///db.sqlite
|
|
||||||
DEBUG=true
|
|
||||||
26
README.md
26
README.md
@ -1,3 +1,25 @@
|
|||||||
# MCP Demo
|
# Codex 重要文件备份
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||||||
|
备份时间: 2026-07-27 14:35:59
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||||||
|
|
||||||
通过远程 MCP Server 推送的代码项目
|
## 目录结构
|
||||||
|
- config/ - 配置文件
|
||||||
|
- skills/ - 技能文件
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||||||
|
- mcp-wrappers/ - MCP 包装器
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||||||
|
- memories/ - 记忆文件
|
||||||
|
- sessions/ - 会话索引
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||||||
|
- projects/ - 项目文件
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||||||
|
|
||||||
|
## 包含的文件
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||||||
|
- config.toml - Codex 配置
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||||||
|
- .env - 环境变量
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||||||
|
- kimi-webbridge - Kimi WebBridge 技能
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||||||
|
- gitea wrapper.js - Gitea MCP 包装器
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||||||
|
- raw_memories.md - 原始记忆
|
||||||
|
- session_index.jsonl - 会话索引
|
||||||
|
|
||||||
|
## 恢复方法
|
||||||
|
1. 复制 config/ 到 ~/.codex/
|
||||||
|
2. 复制 skills/ 到 ~/.codex/skills/
|
||||||
|
3. 复制 mcp-wrappers/ 到 ~/.codex/
|
||||||
|
4. 复制 memories/ 到 ~/.codex/memories/
|
||||||
|
5. 复制 sessions/ 到 ~/.codex/
|
||||||
6
config/.env
Normal file
6
config/.env
Normal file
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|
|||||||
|
NO_PROXY=api.xiaomimimo.com,localhost,127.0.0.1
|
||||||
|
no_proxy=api.xiaomimimo.com,localhost,127.0.0.1
|
||||||
|
HTTP_PROXY=
|
||||||
|
HTTPS_PROXY=
|
||||||
|
http_proxy=
|
||||||
|
https_proxy=
|
||||||
153
config/config.toml
Normal file
153
config/config.toml
Normal file
@ -0,0 +1,153 @@
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|||||||
|
model_provider = "custom"
|
||||||
|
model = "mimo-v2.5"
|
||||||
|
model_catalog_json = "cc-switch-model-catalog.json"
|
||||||
|
web_search = "disabled"
|
||||||
|
notify = ['C:\Users\runst\AppData\Local\OpenAI\Codex\runtimes\cua_node\f8d2abcb7481383b\bin\node_modules\@oai\sky\bin\windows\codex-computer-use.exe', "turn-ended"]
|
||||||
|
model_reasoning_effort = "high"
|
||||||
|
disable_response_storage = true
|
||||||
|
|
||||||
|
[model_providers]
|
||||||
|
|
||||||
|
[windows]
|
||||||
|
sandbox = "elevated"
|
||||||
|
|
||||||
|
[marketplaces.openai-bundled]
|
||||||
|
last_updated = "2026-07-27T05:34:11Z"
|
||||||
|
source_type = "local"
|
||||||
|
source = '\\?\C:\Users\runst\.codex\.tmp\bundled-marketplaces\openai-bundled'
|
||||||
|
[model_providers.custom]
|
||||||
|
name = "xiaomi_mimo"
|
||||||
|
base_url = "https://api.xiaomimimo.com/v1"
|
||||||
|
wire_api = "responses"
|
||||||
|
requires_openai_auth = false
|
||||||
|
experimental_bearer_token = "sk-spjfr1s6j4ya3hpo8y86lku4ldtymcrhse40x4sqa1p1yrkj"
|
||||||
|
|
||||||
|
[marketplaces.openai-curated]
|
||||||
|
source_type = "local"
|
||||||
|
source = '\\?\C:\Users\runst\.codex\.tmp\plugins'
|
||||||
|
|
||||||
|
[marketplaces.openai-api-curated]
|
||||||
|
source_type = "local"
|
||||||
|
source = '\\?\C:\Users\runst\.codex\.tmp\plugins'
|
||||||
|
|
||||||
|
[marketplaces.openai-curated-remote]
|
||||||
|
source_type = "local"
|
||||||
|
source = '\\?\C:\Users\runst\.codex\.tmp\plugins-remote'
|
||||||
|
|
||||||
|
[marketplaces.openai-primary-runtime]
|
||||||
|
last_updated = "2026-07-27T01:09:23Z"
|
||||||
|
source_type = "local"
|
||||||
|
source = '\\?\C:\Users\runst\.cache\codex-runtimes\codex-primary-runtime\plugins\openai-primary-runtime'
|
||||||
|
|
||||||
|
[plugins."documents@openai-primary-runtime"]
|
||||||
|
enabled = true
|
||||||
|
|
||||||
|
[plugins."pdf@openai-primary-runtime"]
|
||||||
|
enabled = true
|
||||||
|
|
||||||
|
[plugins."spreadsheets@openai-primary-runtime"]
|
||||||
|
enabled = true
|
||||||
|
|
||||||
|
[plugins."presentations@openai-primary-runtime"]
|
||||||
|
enabled = true
|
||||||
|
|
||||||
|
[plugins."template-creator@openai-primary-runtime"]
|
||||||
|
enabled = true
|
||||||
|
|
||||||
|
[plugins."browser@openai-bundled"]
|
||||||
|
enabled = true
|
||||||
|
|
||||||
|
[plugins."chrome@openai-bundled"]
|
||||||
|
enabled = true
|
||||||
|
|
||||||
|
[plugins."computer-use@openai-bundled"]
|
||||||
|
enabled = true
|
||||||
|
|
||||||
|
[plugins."visualize@openai-bundled"]
|
||||||
|
enabled = true
|
||||||
|
|
||||||
|
[projects.'c:\users\runst\projects\auto-editor']
|
||||||
|
trust_level = "trusted"
|
||||||
|
|
||||||
|
[projects.'c:\users\runst\documents\codex\2026-06-22\ni-h-6']
|
||||||
|
trust_level = "trusted"
|
||||||
|
|
||||||
|
[projects.'c:\users\runst\documents\cmd']
|
||||||
|
trust_level = "trusted"
|
||||||
|
|
||||||
|
[projects.'c:\users\runst\documents\codex\2026-06-22\ni-h-7']
|
||||||
|
trust_level = "trusted"
|
||||||
|
|
||||||
|
[projects.'c:\users\runst\documents\codex\2026-06-22\ni-h-8']
|
||||||
|
trust_level = "trusted"
|
||||||
|
|
||||||
|
[projects.'c:\users\runst\documents\codex\2026-07-24\new-chat']
|
||||||
|
trust_level = "trusted"
|
||||||
|
|
||||||
|
[projects.'c:\users\runst\documents\codex\2026-07-24\dan']
|
||||||
|
trust_level = "trusted"
|
||||||
|
|
||||||
|
[projects.'c:\users\runst\documents\codex\2026-07-24\ni']
|
||||||
|
trust_level = "trusted"
|
||||||
|
|
||||||
|
[projects.'c:\users\runst']
|
||||||
|
trust_level = "trusted"
|
||||||
|
|
||||||
|
[projects.'c:\users\runst\documents\codex\2026-07-27\nii']
|
||||||
|
trust_level = "trusted"
|
||||||
|
|
||||||
|
[projects.'c:\users\runst\documents\codex\2026-07-27\codex-mcpservers-gitea-type-streamable-http']
|
||||||
|
trust_level = "trusted"
|
||||||
|
|
||||||
|
[features]
|
||||||
|
js_repl = false
|
||||||
|
|
||||||
|
[shell_environment_policy]
|
||||||
|
inherit = "core"
|
||||||
|
|
||||||
|
[shell_environment_policy.set]
|
||||||
|
ANTHROPIC_AUTH_TOKEN = "PROXY_MANAGED"
|
||||||
|
ANTHROPIC_BASE_URL = "http://127.0.0.1:15721"
|
||||||
|
ANTHROPIC_DEFAULT_FABLE_MODEL = "claude-fable-5"
|
||||||
|
ANTHROPIC_DEFAULT_FABLE_MODEL_NAME = "mimo-v2.5"
|
||||||
|
ANTHROPIC_DEFAULT_HAIKU_MODEL = "claude-haiku-4-5"
|
||||||
|
ANTHROPIC_DEFAULT_HAIKU_MODEL_NAME = "mimo-v2.5"
|
||||||
|
ANTHROPIC_DEFAULT_OPUS_MODEL = "claude-opus-4-8"
|
||||||
|
ANTHROPIC_DEFAULT_OPUS_MODEL_NAME = "mimo-v2.5"
|
||||||
|
ANTHROPIC_DEFAULT_SONNET_MODEL = "claude-sonnet-4-6"
|
||||||
|
ANTHROPIC_DEFAULT_SONNET_MODEL_NAME = "mimo-v2.5"
|
||||||
|
CLAUDE_CODE_SUBAGENT_MODEL = "mimo-v2.5-pro"
|
||||||
|
BROWSER_USE_AVAILABLE_BACKENDS = "chrome,iab"
|
||||||
|
NODE_REPL_TRUSTED_BROWSER_CLIENT_SHA256S = "7ed52dae165c3bc22b6d24f282e2c1fbc87f6949fbbe037767a7418d8f517f01,e13fd947e846d3d306e9249dd3c73d14931b6494803dbafb16cef85e6add9506"
|
||||||
|
NODE_REPL_TRUSTED_CODE_PATHS = 'C:\Users\runst\.codex'
|
||||||
|
|
||||||
|
[desktop]
|
||||||
|
followUpQueueMode = "queue"
|
||||||
|
conversationDetailMode = "STEPS_COMMANDS"
|
||||||
|
sansFontSize = 14
|
||||||
|
codeFontSize = 13
|
||||||
|
ambient-suggestions-enabled = false
|
||||||
|
open-local-url-in-target-preference = "external-browser"
|
||||||
|
|
||||||
|
[mcp_servers.node_repl]
|
||||||
|
args = []
|
||||||
|
command = 'C:\codex\Codex\resources\cua_node\bin\node_repl.exe'
|
||||||
|
startup_timeout_sec = 120
|
||||||
|
|
||||||
|
[mcp_servers.node_repl.env]
|
||||||
|
NODE_REPL_NATIVE_PIPE_CONNECT_TIMEOUT_MS = "1000"
|
||||||
|
NODE_REPL_NODE_MODULE_DIRS = 'C:\codex\Codex\resources\cua_node\bin\node_modules'
|
||||||
|
NODE_REPL_NODE_PATH = 'C:\codex\Codex\resources\cua_node\bin\node.exe'
|
||||||
|
NODE_REPL_TRUSTED_CODE_PATHS = 'C:\Users\runst\.codex'
|
||||||
|
CODEX_HOME = 'C:\Users\runst\.codex'
|
||||||
|
NODE_REPL_TRUSTED_BROWSER_CLIENT_SHA256S = "7ed52dae165c3bc22b6d24f282e2c1fbc87f6949fbbe037767a7418d8f517f01,e13fd947e846d3d306e9249dd3c73d14931b6494803dbafb16cef85e6add9506"
|
||||||
|
BROWSER_USE_AVAILABLE_BACKENDS = "chrome,iab"
|
||||||
|
NODE_REPL_INSTRUCTIONS_USE_CASE_BROWSER = "Control the in-app browser in conjunction with the Browser Plugin."
|
||||||
|
NODE_REPL_INSTRUCTIONS_USE_CASE_CHROME = "Control the Chrome browser in conjunction with the Chrome Plugin. Prefer this method of controlling Chrome over alternatives (such as Computer Use) unless the user explicitly mentions an alternative."
|
||||||
|
BROWSER_USE_CODEX_APP_BUILD_FLAVOR = "prod"
|
||||||
|
BROWSER_USE_CODEX_APP_VERSION = "26.721.41059"
|
||||||
|
CODEX_CLI_PATH = 'C:\codex\Codex\resources\codex.exe'
|
||||||
|
|
||||||
|
[mcp_servers.gitea]
|
||||||
|
command = "node"
|
||||||
|
args = ['C:\Users\runst\.codex\mcp-wrappers\gitea\wrapper.js']
|
||||||
@ -1 +0,0 @@
|
|||||||
ok
|
|
||||||
107
mcp-wrappers/gitea/wrapper.js
Normal file
107
mcp-wrappers/gitea/wrapper.js
Normal file
@ -0,0 +1,107 @@
|
|||||||
|
const https = require('https');
|
||||||
|
const { URL } = require('url');
|
||||||
|
|
||||||
|
const REMOTE_URL = 'https://git.aotoagent.com/mcp';
|
||||||
|
const TOKEN = 'gitea-mcp-token-2026';
|
||||||
|
|
||||||
|
let sessionId = null;
|
||||||
|
|
||||||
|
async function sendRequest(body) {
|
||||||
|
return new Promise((resolve, reject) => {
|
||||||
|
const url = new URL(REMOTE_URL);
|
||||||
|
const data = JSON.stringify(body);
|
||||||
|
|
||||||
|
const options = {
|
||||||
|
hostname: url.hostname,
|
||||||
|
port: url.port || 443,
|
||||||
|
path: url.pathname,
|
||||||
|
method: 'POST',
|
||||||
|
headers: {
|
||||||
|
'Content-Type': 'application/json',
|
||||||
|
'Accept': 'application/json, text/event-stream',
|
||||||
|
'Authorization': `Bearer ${TOKEN}`,
|
||||||
|
'Content-Length': Buffer.byteLength(data)
|
||||||
|
}
|
||||||
|
};
|
||||||
|
|
||||||
|
if (sessionId) {
|
||||||
|
options.headers['Mcp-Session-Id'] = sessionId;
|
||||||
|
}
|
||||||
|
|
||||||
|
const req = https.request(options, (res) => {
|
||||||
|
let body = '';
|
||||||
|
res.on('data', (chunk) => body += chunk);
|
||||||
|
res.on('end', () => {
|
||||||
|
if (res.headers['mcp-session-id']) {
|
||||||
|
sessionId = res.headers['mcp-session-id'];
|
||||||
|
}
|
||||||
|
resolve(body);
|
||||||
|
});
|
||||||
|
});
|
||||||
|
|
||||||
|
req.on('error', reject);
|
||||||
|
req.write(data);
|
||||||
|
req.end();
|
||||||
|
});
|
||||||
|
}
|
||||||
|
|
||||||
|
async function main() {
|
||||||
|
let buffer = '';
|
||||||
|
|
||||||
|
process.stdin.on('data', async (chunk) => {
|
||||||
|
buffer += chunk.toString();
|
||||||
|
|
||||||
|
// Process complete lines
|
||||||
|
while (buffer.includes('\n')) {
|
||||||
|
const newlineIndex = buffer.indexOf('\n');
|
||||||
|
const line = buffer.substring(0, newlineIndex).trim();
|
||||||
|
buffer = buffer.substring(newlineIndex + 1);
|
||||||
|
|
||||||
|
if (!line) continue;
|
||||||
|
|
||||||
|
try {
|
||||||
|
const request = JSON.parse(line);
|
||||||
|
const response = await sendRequest(request);
|
||||||
|
|
||||||
|
// Handle SSE format
|
||||||
|
if (response.startsWith('event:')) {
|
||||||
|
const lines = response.split('\n');
|
||||||
|
for (const l of lines) {
|
||||||
|
if (l.startsWith('data:')) {
|
||||||
|
process.stdout.write(l.substring(5).trim() + '\n');
|
||||||
|
}
|
||||||
|
}
|
||||||
|
} else if (response.trim()) {
|
||||||
|
process.stdout.write(response + '\n');
|
||||||
|
}
|
||||||
|
} catch (e) {
|
||||||
|
process.stderr.write(`Error: ${e.message}\n`);
|
||||||
|
}
|
||||||
|
}
|
||||||
|
});
|
||||||
|
|
||||||
|
process.stdin.on('end', () => {
|
||||||
|
// Process any remaining buffer
|
||||||
|
if (buffer.trim()) {
|
||||||
|
try {
|
||||||
|
const request = JSON.parse(buffer.trim());
|
||||||
|
sendRequest(request).then(response => {
|
||||||
|
if (response.startsWith('event:')) {
|
||||||
|
const lines = response.split('\n');
|
||||||
|
for (const l of lines) {
|
||||||
|
if (l.startsWith('data:')) {
|
||||||
|
process.stdout.write(l.substring(5).trim() + '\n');
|
||||||
|
}
|
||||||
|
}
|
||||||
|
} else if (response.trim()) {
|
||||||
|
process.stdout.write(response + '\n');
|
||||||
|
}
|
||||||
|
});
|
||||||
|
} catch (e) {
|
||||||
|
process.stderr.write(`Error: ${e.message}\n`);
|
||||||
|
}
|
||||||
|
}
|
||||||
|
});
|
||||||
|
}
|
||||||
|
|
||||||
|
main();
|
||||||
61
projects/auto-editor/README.md
Normal file
61
projects/auto-editor/README.md
Normal file
@ -0,0 +1,61 @@
|
|||||||
|
# 带货短视频自动化剪辑全链路流水线
|
||||||
|
|
||||||
|
基于分镜头向量检索能力，实现「素材预处理入库 → 口播脚本自动匹配镜头 → 智能剪辑合成 → 成片质检导出」的全链路自动化。
|
||||||
|
|
||||||
|
## 快速开始
|
||||||
|
|
||||||
|
```bash
|
||||||
|
# 1. 安装
|
||||||
|
cd auto-editor
|
||||||
|
pip install -e ".[all]"
|
||||||
|
|
||||||
|
# 2. 配置环境变量
|
||||||
|
cp .env.example .env
|
||||||
|
# 编辑 .env 填入 API Key 等配置
|
||||||
|
|
||||||
|
# 3. 启动 Milvus（需要 Docker）
|
||||||
|
docker compose up -d
|
||||||
|
|
||||||
|
# 4. 素材入库
|
||||||
|
python -m auto_editor.ingest.pipeline --input ./raw_assets --output ./data/hot
|
||||||
|
|
||||||
|
# 5. 生成成片
|
||||||
|
python -m auto_editor.api.server # 启动 API 服务
|
||||||
|
curl -X POST http://localhost:8000/edit \
|
||||||
|
-H "Content-Type: application/json" \
|
||||||
|
-d '{"script": "这款产品效果非常好...", "duration": 30}'
|
||||||
|
```
|
||||||
|
|
||||||
|
## 项目结构
|
||||||
|
|
||||||
|
```
|
||||||
|
auto-editor/
|
||||||
|
├── src/auto_editor/
|
||||||
|
│ ├── core/ # 核心模块：数据模型、FFmpeg、Whisper、元数据
|
||||||
|
│ ├── config/ # 配置管理（Pydantic Settings）
|
||||||
|
│ ├── ingest/ # Phase 1: 素材预处理流水线
|
||||||
|
│ ├── vectorize/ # Phase 2: 向量化引擎
|
||||||
|
│ ├── script_engine/ # Phase 3: 脚本结构化引擎
|
||||||
|
│ ├── retrieval/ # Phase 4: 检索与匹配引擎
|
||||||
|
│ ├── editing/ # Phase 5: 剪辑合成引擎
|
||||||
|
│ ├── packaging/ # Phase 6: 包装与质检
|
||||||
|
│ ├── rules/ # Phase 7: 营销规则引擎
|
||||||
|
│ └── api/ # Phase 8: API 服务层
|
||||||
|
├── configs/ # 规则配置、模型配置
|
||||||
|
├── tests/ # 单元测试
|
||||||
|
└── scripts/ # 运维脚本
|
||||||
|
```
|
||||||
|
|
||||||
|
## 技术栈
|
||||||
|
|
||||||
|
| 组件 | 选型 |
|
||||||
|
|------|------|
|
||||||
|
| 向量模型 | Qwen3-VL-Embedding (DashScope API) |
|
||||||
|
| 向量库 | Milvus 2.x |
|
||||||
|
| 字幕提取 | faster-whisper (本地) |
|
||||||
|
| 镜头检测 | TransNetV2 (本地 GPU) |
|
||||||
|
| 脚本拆分 | Qwen3-8B / 云端 API |
|
||||||
|
| TTS | CosyVoice / GPT-SoVITS / doubao-seed-tts |
|
||||||
|
| 视频处理 | FFmpeg |
|
||||||
|
| 任务队列 | Celery + Redis |
|
||||||
|
| API | FastAPI |
|
||||||
21
projects/auto-editor/package.json
Normal file
21
projects/auto-editor/package.json
Normal file
@ -0,0 +1,21 @@
|
|||||||
|
{
|
||||||
|
"name": "auto-editor-tests",
|
||||||
|
"private": true,
|
||||||
|
"version": "0.1.0",
|
||||||
|
"scripts": {
|
||||||
|
"test": "npx playwright test",
|
||||||
|
"test:ui": "npx playwright test --ui",
|
||||||
|
"test:headed": "npx playwright test --headed",
|
||||||
|
"test:report": "npx playwright show-report",
|
||||||
|
"test:health": "npx playwright test tests/e2e/specs/health.spec.ts",
|
||||||
|
"test:dashboard": "npx playwright test tests/e2e/specs/dashboard.spec.ts",
|
||||||
|
"test:assets": "npx playwright test tests/e2e/specs/assets.spec.ts",
|
||||||
|
"test:editor": "npx playwright test tests/e2e/specs/editor.spec.ts",
|
||||||
|
"test:outputs": "npx playwright test tests/e2e/specs/outputs.spec.ts",
|
||||||
|
"test:rules": "npx playwright test tests/e2e/specs/rules.spec.ts",
|
||||||
|
"test:integration": "npx playwright test tests/e2e/specs/integration.spec.ts"
|
||||||
|
},
|
||||||
|
"devDependencies": {
|
||||||
|
"@playwright/test": "^1.61.1"
|
||||||
|
}
|
||||||
|
}
|
||||||
44
projects/auto-editor/pyproject.toml
Normal file
44
projects/auto-editor/pyproject.toml
Normal file
@ -0,0 +1,44 @@
|
|||||||
|
[project]
|
||||||
|
name = "auto-editor"
|
||||||
|
version = "0.1.0"
|
||||||
|
description = "带货短视频自动化剪辑全链路流水线"
|
||||||
|
requires-python = ">=3.11"
|
||||||
|
dependencies = [
|
||||||
|
"pydantic>=2.0",
|
||||||
|
"pydantic-settings>=2.0",
|
||||||
|
"structlog>=24.0",
|
||||||
|
"celery[redis]>=5.3",
|
||||||
|
"redis>=5.0",
|
||||||
|
"fastapi>=0.110",
|
||||||
|
"uvicorn[standard]>=0.27",
|
||||||
|
"pymilvus>=2.4",
|
||||||
|
"numpy>=1.26",
|
||||||
|
"Pillow>=10.0",
|
||||||
|
]
|
||||||
|
|
||||||
|
[project.optional-dependencies]
|
||||||
|
dev = [
|
||||||
|
"pytest>=8.0",
|
||||||
|
"pytest-asyncio>=0.23",
|
||||||
|
"ruff>=0.3",
|
||||||
|
"mypy>=1.8",
|
||||||
|
]
|
||||||
|
whisper = ["faster-whisper>=1.0"]
|
||||||
|
vectorize = ["volcenginesdkarkruntime>=1.0"]
|
||||||
|
transnet = ["torch>=2.0", "torchvision"]
|
||||||
|
all = ["auto-editor[dev,whisper,vectorize,transnet]"]
|
||||||
|
|
||||||
|
[build-system]
|
||||||
|
requires = ["hatchling"]
|
||||||
|
build-backend = "hatchling.build"
|
||||||
|
|
||||||
|
[tool.ruff]
|
||||||
|
target-version = "py311"
|
||||||
|
line-length = 100
|
||||||
|
|
||||||
|
[tool.ruff.lint]
|
||||||
|
select = ["E", "F", "I", "N", "W", "UP"]
|
||||||
|
|
||||||
|
[tool.mypy]
|
||||||
|
python_version = "3.11"
|
||||||
|
strict = true
|
||||||
48
sessions/session_index.jsonl
Normal file
48
sessions/session_index.jsonl
Normal file
@ -0,0 +1,48 @@
|
|||||||
|
{"id":"019ef39a-459c-72b2-ace9-8cf759bb3e19","thread_name":"检查系统启动项","updated_at":"2026-06-23T08:36:40.579748Z"}
|
||||||
|
{"id":"019f3f89-17c7-7ef2-84de-6fcc192d693f","thread_name":"素材管理","updated_at":"2026-07-08T05:35:31.2151725Z"}
|
||||||
|
{"id":"019f4bc1-d3ba-7f40-9ceb-f58cc3c141eb","thread_name":"https://www.autodl.com/docs/ 查看文档","updated_at":"2026-07-10T11:21:02.0484383Z"}
|
||||||
|
{"id":"019f4bdf-f887-7f73-a7a1-2ece7d8668a9","thread_name":"搜索视频换口型，效果比较好的工具","updated_at":"2026-07-10T11:53:46.8796048Z"}
|
||||||
|
{"id":"019f5e3a-b9c9-75f1-b822-16ab9f840c29","thread_name":"检查终端claude和hermes是否正确安装","updated_at":"2026-07-14T01:25:55.3789929Z"}
|
||||||
|
{"id":"019f5e3d-5301-7371-aa31-0f06658c37ec","thread_name":"检查powershell是否是最新版本","updated_at":"2026-07-14T01:28:25.5407985Z"}
|
||||||
|
{"id":"019f8d9d-1659-7f41-ab3a-3fa7f2aa8f07","thread_name":"查看当前项目","updated_at":"2026-07-23T06:15:20.4592316Z"}
|
||||||
|
{"id":"019f8dce-d9fd-7551-8e8d-1a352e21331c","thread_name":"检查浏览器插件是否正常","updated_at":"2026-07-23T07:09:42.4323109Z"}
|
||||||
|
{"id":"019f40a7-49fe-7a60-ac36-86014b44b097","thread_name":"视频协作","updated_at":"2026-07-23T08:07:08.4257481Z"}
|
||||||
|
{"id":"019f46c5-ae1f-7051-b8e4-9a8ee0b97e11","thread_name":"mimo语音克隆","updated_at":"2026-07-23T08:07:26.1880068Z"}
|
||||||
|
{"id":"019f8e05-e990-7c32-868b-75304bad70cd","thread_name":"github搜索是否有开源项目和当前项目相似","updated_at":"2026-07-23T08:10:14.1189618Z"}
|
||||||
|
{"id":"019f8e05-e990-7c32-868b-75304bad70cd","thread_name":"MoviePy","updated_at":"2026-07-23T08:21:45.7961758Z"}
|
||||||
|
{"id":"019f8e11-294d-7bf2-b676-082711acc172","thread_name":"github搜索开源的可视化剪辑项目，支持mcp和当前项目可以集成的","updated_at":"2026-07-23T08:22:17.9255432Z"}
|
||||||
|
{"id":"019f8e16-26b3-7532-937b-873fa5857602","thread_name":"codex桌面端是否有移动端可以连接，或者连接即使通讯及时看到项目进度","updated_at":"2026-07-23T08:27:58.452372Z"}
|
||||||
|
{"id":"019f8e11-294d-7bf2-b676-082711acc172","thread_name":"FableCut","updated_at":"2026-07-23T08:28:39.5772042Z"}
|
||||||
|
{"id":"019f8e2a-46c3-7241-8bf0-2d2079d89a96","thread_name":"github搜索优化视频理解，降低视觉理解模型，节约token的开源项目","updated_at":"2026-07-23T08:49:47.873974Z"}
|
||||||
|
{"id":"019f8e2a-46c3-7241-8bf0-2d2079d89a96","thread_name":"节约视频token","updated_at":"2026-07-23T08:50:07.9211817Z"}
|
||||||
|
{"id":"019f8d9d-1659-7f41-ab3a-3fa7f2aa8f07","thread_name":"项目开发","updated_at":"2026-07-23T09:23:29.5439614Z"}
|
||||||
|
{"id":"019f8e49-94c7-7962-b9d5-6ed14438c084","thread_name":"检查当前项目，如何预处理视频，ai分析的时候，节约token","updated_at":"2026-07-23T09:24:03.526669Z"}
|
||||||
|
{"id":"019f8e49-94c7-7962-b9d5-6ed14438c084","thread_name":"节省token","updated_at":"2026-07-23T09:24:09.6424099Z"}
|
||||||
|
{"id":"019f8e6a-b963-73d3-aeb7-03d9d989c802","thread_name":"github搜索场景检测用什么开源项目","updated_at":"2026-07-23T10:00:20.4266029Z"}
|
||||||
|
{"id":"019f8f4a-483c-7a41-a632-1ac186d5336f","thread_name":"你好","updated_at":"2026-07-23T14:04:00.3100798Z"}
|
||||||
|
{"id":"019f8f50-58cc-77e0-92c9-b9f3160c7ceb","thread_name":"查看codex搜索能力是否正常","updated_at":"2026-07-23T14:10:49.6424437Z"}
|
||||||
|
{"id":"019f9193-e5fd-72e1-a165-d953d77da4ea","thread_name":"github搜搜支持中文界面的开源剪辑项目","updated_at":"2026-07-24T00:44:01.5585598Z"}
|
||||||
|
{"id":"019f9200-4c27-72e0-ae4b-8257272c0c52","thread_name":"@浏览器 打开浏览器，搜索今天天气","updated_at":"2026-07-24T02:42:24.4609023Z"}
|
||||||
|
{"id":"019f927e-65bf-7152-bce5-f862a7a31549","thread_name":"https://www.kimi.com/zh-cn/features/webbridge 安装","updated_at":"2026-07-24T04:59:47.4778147Z"}
|
||||||
|
{"id":"019f92fa-75bf-7d60-a043-ab45ac87dc4f","thread_name":"当前是最新的版本嘛","updated_at":"2026-07-24T07:15:26.6763639Z"}
|
||||||
|
{"id":"019f9304-dba2-7e82-aa97-3d784b995548","thread_name":"你是","updated_at":"2026-07-24T07:26:41.4268324Z"}
|
||||||
|
{"id":"019f932d-1208-7802-8b7f-dc6b2f2d4d6c","thread_name":"https://learn atgpt.com/docs/sandboxing#how-you-control-it…","updated_at":"2026-07-24T08:10:41.3713194Z"}
|
||||||
|
{"id":"019f932d-e3f5-7ce2-89a3-e00043ec314f","thread_name":"https://learn.chatgpt.com/docs/sandboxing#how-you-control-i…","updated_at":"2026-07-24T08:11:38.0512937Z"}
|
||||||
|
{"id":"019f9346-c63f-7fa2-8b7f-87f7962f971f","thread_name":"@chrome file my expenses for me 自动化测试项目","updated_at":"2026-07-24T08:39:47.937717Z"}
|
||||||
|
{"id":"019f9353-3bd7-7f63-bf34-d37513748e45","thread_name":"Kimi WebBridge 是否正确使用","updated_at":"2026-07-24T08:52:21.4724843Z"}
|
||||||
|
{"id":"019f935c-3d38-7e50-8f6f-464ad0abb853","thread_name":"@电脑 打开豆包，搜索天气","updated_at":"2026-07-24T09:02:33.22883Z"}
|
||||||
|
{"id":"019f938c-a8c3-78b3-b48e-53016c4e234a","thread_name":"@电脑 Play a playlist to help me lock in 打开记事本，记录今天的天气","updated_at":"2026-07-24T09:55:12.4609991Z"}
|
||||||
|
{"id":"019f938f-5db8-7bb0-9aa5-2aa73817e5bf","thread_name":"@电脑 打开网页，查看今天的天气","updated_at":"2026-07-24T09:58:01.9043052Z"}
|
||||||
|
{"id":"019f93b6-791b-7d92-8a5a-4f5ac7aadbd0","thread_name":"github搜索剪辑软件前端设计ui","updated_at":"2026-07-24T10:41:08.5991317Z"}
|
||||||
|
{"id":"019f93c4-5041-76d3-a96a-e0b79f261f80","thread_name":"github搜索剪映的前端ui设计","updated_at":"2026-07-24T10:55:55.8763804Z"}
|
||||||
|
{"id":"019f93c6-f8f7-7d33-b170-5e7e003a9c5a","thread_name":"github搜索剪映的前端ui设计","updated_at":"2026-07-24T10:58:38.5539866Z"}
|
||||||
|
{"id":"019f93c6-f8f7-7d33-b170-5e7e003a9c5a","thread_name":"github搜索剪映的前端ui设计 (2)","updated_at":"2026-07-24T10:58:39.7170484Z"}
|
||||||
|
{"id":"019f9353-3bd7-7f63-bf34-d37513748e45","thread_name":"Kimi WebBridge","updated_at":"2026-07-24T13:28:57.4761712Z"}
|
||||||
|
{"id":"019f949f-89d6-7503-9734-19a1be881519","thread_name":"需要根据当前图片1比1还原成一个设计图","updated_at":"2026-07-24T14:55:27.2294478Z"}
|
||||||
|
{"id":"019f94a0-5982-7d63-ba5b-aafff117936f","thread_name":"@product-design Help me get started，需要1比1设计原型图","updated_at":"2026-07-24T14:56:25.94396Z"}
|
||||||
|
{"id":"019f9760-a454-7680-8549-2de72321b923","thread_name":"将这张1图片上的所以按钮和功能ui布局，标注详细的大小和尺寸，等详细的数据","updated_at":"2026-07-25T03:46:07.4280822Z"}
|
||||||
|
{"id":"019f988a-d585-7942-9e69-a1c8f794b3db","thread_name":"github搜索chatcut 安装部署","updated_at":"2026-07-25T09:11:29.384115Z"}
|
||||||
|
{"id":"019fa097-9faf-72b2-abe2-3c613686fd14","thread_name":"配置当前mcp Gitea MCP 最新配置 Claude Code 配置（~/.claude.json） { \"mc…","updated_at":"2026-07-26T22:42:08.6882342Z"}
|
||||||
|
{"id":"019fa11e-85a1-7280-8783-21fc5e113909","thread_name":"你好","updated_at":"2026-07-27T01:09:25.2124385Z"}
|
||||||
|
{"id":"019fa1c2-7b6c-7f71-b0d6-da8c1bdd461c","thread_name":"Codex 桌面端： { \"mcpServers\": { \"gitea\": { \"type\": \"streamable…","updated_at":"2026-07-27T04:08:33.6799348Z"}
|
||||||
|
{"id":"019fa1c2-7b6c-7f71-b0d6-da8c1bdd461c","thread_name":"gitmcp","updated_at":"2026-07-27T04:09:10.6623906Z"}
|
||||||
1
skills/.system/.codex-system-skills.marker
Normal file
1
skills/.system/.codex-system-skills.marker
Normal file
@ -0,0 +1 @@
|
|||||||
|
4d054d116c71fb34
|
||||||
201
skills/.system/imagegen/LICENSE.txt
Normal file
201
skills/.system/imagegen/LICENSE.txt
Normal file
@ -0,0 +1,201 @@
|
|||||||
|
Apache License
|
||||||
|
Version 2.0, January 2004
|
||||||
|
http://www.apache.org/licenses/
|
||||||
|
|
||||||
|
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
|
||||||
|
|
||||||
|
1. Definitions.
|
||||||
|
|
||||||
|
"License" shall mean the terms and conditions for use, reproduction,
|
||||||
|
and distribution as defined by Sections 1 through 9 of this document.
|
||||||
|
|
||||||
|
"Licensor" shall mean the copyright owner or entity authorized by
|
||||||
|
the copyright owner that is granting the License.
|
||||||
|
|
||||||
|
"Legal Entity" shall mean the union of the acting entity and all
|
||||||
|
other entities that control, are controlled by, or are under common
|
||||||
|
control with that entity. For the purposes of this definition,
|
||||||
|
"control" means (i) the power, direct or indirect, to cause the
|
||||||
|
direction or management of such entity, whether by contract or
|
||||||
|
otherwise, or (ii) ownership of fifty percent (50%) or more of the
|
||||||
|
outstanding shares, or (iii) beneficial ownership of such entity.
|
||||||
|
|
||||||
|
"You" (or "Your") shall mean an individual or Legal Entity
|
||||||
|
exercising permissions granted by this License.
|
||||||
|
|
||||||
|
"Source" form shall mean the preferred form for making modifications,
|
||||||
|
including but not limited to software source code, documentation
|
||||||
|
source, and configuration files.
|
||||||
|
|
||||||
|
"Object" form shall mean any form resulting from mechanical
|
||||||
|
transformation or translation of a Source form, including but
|
||||||
|
not limited to compiled object code, generated documentation,
|
||||||
|
and conversions to other media types.
|
||||||
|
|
||||||
|
"Work" shall mean the work of authorship, whether in Source or
|
||||||
|
Object form, made available under the License, as indicated by a
|
||||||
|
copyright notice that is included in or attached to the work
|
||||||
|
(an example is provided in the Appendix below).
|
||||||
|
|
||||||
|
"Derivative Works" shall mean any work, whether in Source or Object
|
||||||
|
form, that is based on (or derived from) the Work and for which the
|
||||||
|
editorial revisions, annotations, elaborations, or other modifications
|
||||||
|
represent, as a whole, an original work of authorship. For the purposes
|
||||||
|
of this License, Derivative Works shall not include works that remain
|
||||||
|
separable from, or merely link (or bind by name) to the interfaces of,
|
||||||
|
the Work and Derivative Works thereof.
|
||||||
|
|
||||||
|
"Contribution" shall mean any work of authorship, including
|
||||||
|
the original version of the Work and any modifications or additions
|
||||||
|
to that Work or Derivative Works thereof, that is intentionally
|
||||||
|
submitted to Licensor for inclusion in the Work by the copyright owner
|
||||||
|
or by an individual or Legal Entity authorized to submit on behalf of
|
||||||
|
the copyright owner. For the purposes of this definition, "submitted"
|
||||||
|
means any form of electronic, verbal, or written communication sent
|
||||||
|
to the Licensor or its representatives, including but not limited to
|
||||||
|
communication on electronic mailing lists, source code control systems,
|
||||||
|
and issue tracking systems that are managed by, or on behalf of, the
|
||||||
|
Licensor for the purpose of discussing and improving the Work, but
|
||||||
|
excluding communication that is conspicuously marked or otherwise
|
||||||
|
designated in writing by the copyright owner as "Not a Contribution."
|
||||||
|
|
||||||
|
"Contributor" shall mean Licensor and any individual or Legal Entity
|
||||||
|
on behalf of whom a Contribution has been received by Licensor and
|
||||||
|
subsequently incorporated within the Work.
|
||||||
|
|
||||||
|
2. Grant of Copyright License. Subject to the terms and conditions of
|
||||||
|
this License, each Contributor hereby grants to You a perpetual,
|
||||||
|
worldwide, non-exclusive, no-charge, royalty-free, irrevocable
|
||||||
|
copyright license to reproduce, prepare Derivative Works of,
|
||||||
|
publicly display, publicly perform, sublicense, and distribute the
|
||||||
|
Work and such Derivative Works in Source or Object form.
|
||||||
|
|
||||||
|
3. Grant of Patent License. Subject to the terms and conditions of
|
||||||
|
this License, each Contributor hereby grants to You a perpetual,
|
||||||
|
worldwide, non-exclusive, no-charge, royalty-free, irrevocable
|
||||||
|
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|
||||||
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|
||||||
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||||||
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||||||
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|
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||||||
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||||||
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||||||
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||||||
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||||||
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||||||
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|
||||||
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|
||||||
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||||||
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||||||
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|
||||||
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||||||
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|
||||||
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||||||
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||||||
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(d) If the Work includes a "NOTICE" text file as part of its
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||||||
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||||||
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||||||
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do not modify the License. You may add Your own attribution
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||||||
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You may add Your own copyright statement to Your modifications and
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||||||
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5. Submission of Contributions. Unless You explicitly state otherwise,
|
||||||
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END OF TERMS AND CONDITIONS
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|
||||||
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APPENDIX: How to apply the Apache License to your work.
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||||||
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|
||||||
|
To apply the Apache License to your work, attach the following
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||||||
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||||||
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||||||
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|
||||||
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||||||
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|
||||||
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||||||
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|
||||||
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||||||
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|
||||||
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||||||
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|
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||||||
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||||||
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||||||
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|
||||||
|
See the License for the specific language governing permissions and
|
||||||
|
limitations under the License.
|
||||||
356
skills/.system/imagegen/SKILL.md
Normal file
356
skills/.system/imagegen/SKILL.md
Normal file
@ -0,0 +1,356 @@
|
|||||||
|
---
|
||||||
|
name: "imagegen"
|
||||||
|
description: "Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output should be a bitmap asset rather than repo-native code or vector. Do not use when the task is better handled by editing existing SVG/vector/code-native assets, extending an established icon or logo system, or building the visual directly in HTML/CSS/canvas."
|
||||||
|
---
|
||||||
|
|
||||||
|
# Image Generation Skill
|
||||||
|
|
||||||
|
Generates or edits images for the current project (for example website assets, game assets, UI mockups, product mockups, wireframes, logo design, photorealistic images, or infographics).
|
||||||
|
|
||||||
|
## Top-level modes and rules
|
||||||
|
|
||||||
|
This skill has exactly two top-level modes:
|
||||||
|
|
||||||
|
- **Default built-in tool mode (preferred):** built-in `image_gen` tool for normal image generation, editing, and simple transparent-image requests. Does not require `OPENAI_API_KEY`.
|
||||||
|
- **Fallback CLI mode:** `scripts/image_gen.py` CLI. Use when the user explicitly asks for the CLI/API/model path, or after the user explicitly confirms a true model-native transparency fallback with `gpt-image-1.5`. Requires `OPENAI_API_KEY`.
|
||||||
|
|
||||||
|
Within CLI fallback, the CLI exposes three subcommands:
|
||||||
|
|
||||||
|
- `generate`
|
||||||
|
- `edit`
|
||||||
|
- `generate-batch`
|
||||||
|
|
||||||
|
Rules:
|
||||||
|
- Use the built-in `image_gen` tool by default for normal image generation and editing requests.
|
||||||
|
- Do not switch to CLI fallback for ordinary quality, size, or file-path control.
|
||||||
|
- If the user explicitly asks for a transparent image/background, stay on built-in `image_gen` first: prompt for a flat removable chroma-key background, then remove it locally with the installed helper at `$CODEX_HOME/skills/.system/imagegen/scripts/remove_chroma_key.py`.
|
||||||
|
- Never silently switch from built-in `image_gen` or CLI `gpt-image-2` to CLI `gpt-image-1.5`. Treat this as a model/path downgrade and ask the user before doing it, unless the user has already explicitly requested `gpt-image-1.5`, `scripts/image_gen.py`, or CLI fallback.
|
||||||
|
- If a transparent request appears too complex for clean chroma-key removal, asks for true/native transparency, or local removal fails validation, explain that true transparency requires CLI `gpt-image-1.5 --background transparent --output-format png` because `gpt-image-2` does not support `background=transparent`, then ask whether to proceed. Run the CLI fallback only after the user confirms.
|
||||||
|
- The word `batch` by itself does not mean CLI fallback. If the user asks for many assets or says to batch-generate assets without explicitly asking for CLI/API/model controls, stay on the built-in path and issue one built-in call per requested asset or variant.
|
||||||
|
- If the built-in tool fails or is unavailable, tell the user the CLI fallback exists and that it requires `OPENAI_API_KEY`. Proceed only if the user explicitly asks for that fallback.
|
||||||
|
- If the user explicitly asks for CLI mode, use the bundled `scripts/image_gen.py` workflow. Do not create one-off SDK runners.
|
||||||
|
- Never modify `scripts/image_gen.py`. If something is missing, ask the user before doing anything else.
|
||||||
|
|
||||||
|
Built-in save-path policy:
|
||||||
|
- In built-in tool mode, Codex saves generated images under `$CODEX_HOME/*` by default.
|
||||||
|
- Do not describe or rely on OS temp as the default built-in destination.
|
||||||
|
- Do not describe or rely on a destination-path argument (if any) on the built-in `image_gen` tool. If a specific location is needed, generate first and then move or copy the selected output from `$CODEX_HOME/generated_images/...`.
|
||||||
|
- Save-path precedence in built-in mode:
|
||||||
|
1. If the user names a destination, move or copy the selected output there.
|
||||||
|
2. If the image is meant for the current project, move or copy the final selected image into the workspace before finishing.
|
||||||
|
3. If the image is only for preview or brainstorming, render it inline; the underlying file can remain at the default `$CODEX_HOME/*` path.
|
||||||
|
- Never leave a project-referenced asset only at the default `$CODEX_HOME/*` path.
|
||||||
|
- Do not overwrite an existing asset unless the user explicitly asked for replacement; otherwise create a sibling versioned filename such as `hero-v2.png` or `item-icon-edited.png`.
|
||||||
|
|
||||||
|
Shared prompt guidance for both modes lives in `references/prompting.md` and `references/sample-prompts.md`.
|
||||||
|
|
||||||
|
Fallback-only docs/resources for CLI mode:
|
||||||
|
- `references/cli.md`
|
||||||
|
- `references/image-api.md`
|
||||||
|
- `references/codex-network.md`
|
||||||
|
- `scripts/image_gen.py`
|
||||||
|
|
||||||
|
Local post-processing helper:
|
||||||
|
- `$CODEX_HOME/skills/.system/imagegen/scripts/remove_chroma_key.py`: removes a flat chroma-key background from a generated image and writes a PNG/WebP with alpha. Prefer auto-key sampling, soft matte, and despill for antialiased edges.
|
||||||
|
|
||||||
|
## When to use
|
||||||
|
- Generate a new image (concept art, product shot, cover, website hero)
|
||||||
|
- Generate a new image using one or more reference images for style, composition, or mood
|
||||||
|
- Edit an existing image (inpainting, lighting or weather transformations, background replacement, object removal, compositing, transparent background)
|
||||||
|
- Produce many assets or variants for one task
|
||||||
|
|
||||||
|
## When not to use
|
||||||
|
- Extending or matching an existing SVG/vector icon set, logo system, or illustration library inside the repo
|
||||||
|
- Creating simple shapes, diagrams, wireframes, or icons that are better produced directly in SVG, HTML/CSS, or canvas
|
||||||
|
- Making a small project-local asset edit when the source file already exists in an editable native format
|
||||||
|
- Any task where the user clearly wants deterministic code-native output instead of a generated bitmap
|
||||||
|
|
||||||
|
## Decision tree
|
||||||
|
|
||||||
|
Think about two separate questions:
|
||||||
|
|
||||||
|
1. **Intent:** is this a new image or an edit of an existing image?
|
||||||
|
2. **Execution strategy:** is this one asset or many assets/variants?
|
||||||
|
|
||||||
|
Intent:
|
||||||
|
- If the user wants to modify an existing image while preserving parts of it, treat the request as **edit**.
|
||||||
|
- If the user provides images only as references for style, composition, mood, or subject guidance, treat the request as **generate**.
|
||||||
|
- If the user provides no images, treat the request as **generate**.
|
||||||
|
|
||||||
|
Built-in edit semantics:
|
||||||
|
- Built-in edit mode is for images already visible in the conversation context, such as attached images or images generated earlier in the thread.
|
||||||
|
- If the user wants to edit a local image file with the built-in tool, first load it with built-in `view_image` tool so the image is visible in the conversation context, then proceed with the built-in edit flow.
|
||||||
|
- Do not promise arbitrary filesystem-path editing through the built-in tool.
|
||||||
|
- If a local file still needs direct file-path control, masks, or other explicit CLI-only parameters, use the explicit CLI fallback only when the user asks for it.
|
||||||
|
- For edits, preserve invariants aggressively and save non-destructively by default.
|
||||||
|
|
||||||
|
Execution strategy:
|
||||||
|
- In the built-in default path, produce many assets or variants by issuing one `image_gen` call per requested asset or variant.
|
||||||
|
- In the CLI fallback path, use the CLI `generate-batch` subcommand only when the user explicitly chose CLI mode and needs many prompts/assets.
|
||||||
|
- For many distinct assets, do not use `n` as a substitute for separate prompts. `n` is for variants of one prompt; distinct assets need distinct built-in calls or distinct CLI `generate-batch` jobs.
|
||||||
|
|
||||||
|
Assume the user wants a new image unless they clearly ask to change an existing one.
|
||||||
|
|
||||||
|
## Workflow
|
||||||
|
1. Decide the top-level mode: built-in by default, including simple transparent-output requests; fallback CLI only if explicitly requested or after the user explicitly confirms a transparent-output fallback.
|
||||||
|
2. Decide the intent: `generate` or `edit`.
|
||||||
|
3. Decide whether the output is preview-only or meant to be consumed by the current project.
|
||||||
|
4. Decide the execution strategy: single asset vs repeated built-in calls vs CLI `generate-batch`.
|
||||||
|
5. Collect inputs up front: prompt(s), exact text (verbatim), constraints/avoid list, and any input images.
|
||||||
|
6. For every input image, label its role explicitly:
|
||||||
|
- reference image
|
||||||
|
- edit target
|
||||||
|
- supporting insert/style/compositing input
|
||||||
|
7. If the edit target is only on the local filesystem and you are staying on the built-in path, inspect it with `view_image` first so the image is available in conversation context.
|
||||||
|
8. If the user asked for a photo, illustration, sprite, product image, banner, or other explicitly raster-style asset, use `image_gen` rather than substituting SVG/HTML/CSS placeholders. If the request is for an icon, logo, or UI graphic that should match existing repo-native SVG/vector/code assets, prefer editing those directly instead.
|
||||||
|
9. Augment the prompt based on specificity:
|
||||||
|
- If the user's prompt is already specific and detailed, normalize it into a clear spec without adding creative requirements.
|
||||||
|
- If the user's prompt is generic, add tasteful augmentation only when it materially improves output quality.
|
||||||
|
10. Use the built-in `image_gen` tool by default.
|
||||||
|
11. For transparent-output requests, follow the transparent image guidance below: generate with built-in `image_gen` on a flat chroma-key background, copy the selected output into the workspace or `tmp/imagegen/`, run the installed `$CODEX_HOME/skills/.system/imagegen/scripts/remove_chroma_key.py` helper, and validate the alpha result before using it. If this path looks unsuitable or fails, ask before switching to CLI `gpt-image-1.5`.
|
||||||
|
12. Inspect outputs and validate: subject, style, composition, text accuracy, and invariants/avoid items.
|
||||||
|
13. Iterate with a single targeted change, then re-check.
|
||||||
|
14. For preview-only work, render the image inline; the underlying file may remain at the default `$CODEX_HOME/generated_images/...` path.
|
||||||
|
15. For project-bound work, move or copy the selected artifact into the workspace and update any consuming code or references. Never leave a project-referenced asset only at the default `$CODEX_HOME/generated_images/...` path.
|
||||||
|
16. For batches or multi-asset requests, persist every requested deliverable final in the workspace unless the user explicitly asked to keep outputs preview-only. Discarded variants do not need to be kept unless requested.
|
||||||
|
17. If the user explicitly chooses or confirms the CLI fallback, then use the fallback-only docs for model, quality, size, `input_fidelity`, masks, output format, output paths, and network setup.
|
||||||
|
18. Always report the final saved path(s) for any workspace-bound asset(s), plus the final prompt or prompt set and whether the built-in tool or fallback CLI mode was used.
|
||||||
|
|
||||||
|
## Transparent image requests
|
||||||
|
|
||||||
|
Transparent-image requests still use built-in `image_gen` first. Because the built-in tool does not expose a true transparent-background control, create a removable chroma-key source image and then convert the key color to alpha locally.
|
||||||
|
|
||||||
|
Default sequence:
|
||||||
|
1. Use built-in `image_gen` to generate the requested subject on a perfectly flat solid chroma-key background.
|
||||||
|
2. Choose a key color that is unlikely to appear in the subject: default `#00ff00`, use `#ff00ff` for green subjects, and avoid `#0000ff` for blue subjects.
|
||||||
|
3. After generation, move or copy the selected source image from `$CODEX_HOME/generated_images/...` into the workspace or `tmp/imagegen/`.
|
||||||
|
4. Run the installed helper path, not a project-relative script path:
|
||||||
|
```bash
|
||||||
|
python "${CODEX_HOME:-$HOME/.codex}/skills/.system/imagegen/scripts/remove_chroma_key.py" \
|
||||||
|
--input <source> \
|
||||||
|
--out <final.png> \
|
||||||
|
--auto-key border \
|
||||||
|
--soft-matte \
|
||||||
|
--transparent-threshold 12 \
|
||||||
|
--opaque-threshold 220 \
|
||||||
|
--despill
|
||||||
|
```
|
||||||
|
5. Validate that the output has an alpha channel, transparent corners, plausible subject coverage, and no obvious key-color fringe. If a thin fringe remains, retry once with `--edge-contract 1`; use `--edge-feather 0.25` only when the edge is visibly stair-stepped and the subject is not shiny or reflective.
|
||||||
|
6. Save the final alpha PNG/WebP in the project if the asset is project-bound. Never leave a project-referenced transparent asset only under `$CODEX_HOME/*`.
|
||||||
|
|
||||||
|
Prompt transparent requests like this:
|
||||||
|
|
||||||
|
```text
|
||||||
|
Create the requested subject on a perfectly flat solid #00ff00 chroma-key background for background removal.
|
||||||
|
The background must be one uniform color with no shadows, gradients, texture, reflections, floor plane, or lighting variation.
|
||||||
|
Keep the subject fully separated from the background with crisp edges and generous padding.
|
||||||
|
Do not use #00ff00 anywhere in the subject.
|
||||||
|
No cast shadow, no contact shadow, no reflection, no watermark, and no text unless explicitly requested.
|
||||||
|
```
|
||||||
|
|
||||||
|
Do not automatically use CLI `gpt-image-1.5 --background transparent --output-format png` instead of chroma keying. Ask the user first when the user asks for true/native transparency, when local removal fails validation, or when the requested image is complex: hair, fur, feathers, smoke, glass, liquids, translucent materials, reflective objects, soft shadows, realistic product grounding, or subject colors that conflict with all practical key colors.
|
||||||
|
|
||||||
|
Use a concise confirmation like:
|
||||||
|
|
||||||
|
```text
|
||||||
|
This likely needs true native transparency. The default built-in path uses a chroma-key background plus local removal, but true transparency requires the CLI fallback with gpt-image-1.5 because gpt-image-2 does not support background=transparent. It also requires OPENAI_API_KEY. Should I proceed with that CLI fallback?
|
||||||
|
```
|
||||||
|
|
||||||
|
## Prompt augmentation
|
||||||
|
|
||||||
|
Reformat user prompts into a structured, production-oriented spec. Make the user's goal clearer and more actionable, but do not blindly add detail.
|
||||||
|
|
||||||
|
Treat this as prompt-shaping guidance, not a closed schema. Use only the lines that help, and add a short extra labeled line when it materially improves clarity.
|
||||||
|
|
||||||
|
### Specificity policy
|
||||||
|
|
||||||
|
Use the user's prompt specificity to decide how much augmentation is appropriate:
|
||||||
|
|
||||||
|
- If the prompt is already specific and detailed, preserve that specificity and only normalize/structure it.
|
||||||
|
- If the prompt is generic, you may add tasteful augmentation when it will materially improve the result.
|
||||||
|
|
||||||
|
Allowed augmentations:
|
||||||
|
- composition or framing hints
|
||||||
|
- polish level or intended-use hints
|
||||||
|
- practical layout guidance
|
||||||
|
- reasonable scene concreteness that supports the stated request
|
||||||
|
|
||||||
|
Not allowed augmentations:
|
||||||
|
- extra characters or objects that are not implied by the request
|
||||||
|
- brand names, slogans, palettes, or narrative beats that are not implied
|
||||||
|
- arbitrary side-specific placement unless the surrounding layout supports it
|
||||||
|
|
||||||
|
## Use-case taxonomy (exact slugs)
|
||||||
|
|
||||||
|
Classify each request into one of these buckets and keep the slug consistent across prompts and references.
|
||||||
|
|
||||||
|
Generate:
|
||||||
|
- photorealistic-natural — candid/editorial lifestyle scenes with real texture and natural lighting.
|
||||||
|
- product-mockup — product/packaging shots, catalog imagery, merch concepts.
|
||||||
|
- ui-mockup — app/web interface mockups and wireframes; specify the desired fidelity.
|
||||||
|
- infographic-diagram — diagrams/infographics with structured layout and text.
|
||||||
|
- scientific-educational — classroom explainers, scientific diagrams, and learning visuals with required labels and accuracy constraints.
|
||||||
|
- ads-marketing — campaign concepts and ad creatives with audience, brand position, scene, and exact tagline/copy.
|
||||||
|
- productivity-visual — slide, chart, workflow, and data-heavy business visuals.
|
||||||
|
- logo-brand — logo/mark exploration, vector-friendly.
|
||||||
|
- illustration-story — comics, children’s book art, narrative scenes.
|
||||||
|
- stylized-concept — style-driven concept art, 3D/stylized renders.
|
||||||
|
- historical-scene — period-accurate/world-knowledge scenes.
|
||||||
|
|
||||||
|
Edit:
|
||||||
|
- text-localization — translate/replace in-image text, preserve layout.
|
||||||
|
- identity-preserve — try-on, person-in-scene; lock face/body/pose.
|
||||||
|
- precise-object-edit — remove/replace a specific element (including interior swaps).
|
||||||
|
- lighting-weather — time-of-day/season/atmosphere changes only.
|
||||||
|
- background-extraction — transparent background / clean cutout. Use built-in `image_gen` with chroma-key removal first for simple opaque subjects; ask before using CLI true transparency for complex subjects.
|
||||||
|
- style-transfer — apply reference style while changing subject/scene.
|
||||||
|
- compositing — multi-image insert/merge with matched lighting/perspective.
|
||||||
|
- sketch-to-render — drawing/line art to photoreal render.
|
||||||
|
|
||||||
|
## Shared prompt schema
|
||||||
|
|
||||||
|
Use the following labeled spec as shared prompt scaffolding for both top-level modes:
|
||||||
|
|
||||||
|
```text
|
||||||
|
Use case: <taxonomy slug>
|
||||||
|
Asset type: <where the asset will be used>
|
||||||
|
Primary request: <user's main prompt>
|
||||||
|
Input images: <Image 1: role; Image 2: role> (optional)
|
||||||
|
Scene/backdrop: <environment>
|
||||||
|
Subject: <main subject>
|
||||||
|
Style/medium: <photo/illustration/3D/etc>
|
||||||
|
Composition/framing: <wide/close/top-down; placement>
|
||||||
|
Lighting/mood: <lighting + mood>
|
||||||
|
Color palette: <palette notes>
|
||||||
|
Materials/textures: <surface details>
|
||||||
|
Text (verbatim): "<exact text>"
|
||||||
|
Constraints: <must keep/must avoid>
|
||||||
|
Avoid: <negative constraints>
|
||||||
|
```
|
||||||
|
|
||||||
|
Notes:
|
||||||
|
- `Asset type` and `Input images` are prompt scaffolding, not dedicated CLI flags.
|
||||||
|
- `Scene/backdrop` refers to the visual setting. It is not the same as the fallback CLI `background` parameter, which controls output transparency behavior.
|
||||||
|
- Fallback-only execution notes such as `Quality:`, `Input fidelity:`, masks, output format, and output paths belong in the CLI path only. Do not treat them as built-in `image_gen` tool arguments.
|
||||||
|
|
||||||
|
Augmentation rules:
|
||||||
|
- Keep it short.
|
||||||
|
- Add only the details needed to improve the prompt materially.
|
||||||
|
- For edits, explicitly list invariants (`change only X; keep Y unchanged`).
|
||||||
|
- If any critical detail is missing and blocks success, ask a question; otherwise proceed.
|
||||||
|
|
||||||
|
## Examples
|
||||||
|
|
||||||
|
### Generation example (hero image)
|
||||||
|
```text
|
||||||
|
Use case: product-mockup
|
||||||
|
Asset type: landing page hero
|
||||||
|
Primary request: a minimal hero image of a ceramic coffee mug
|
||||||
|
Style/medium: clean product photography
|
||||||
|
Composition/framing: wide composition with usable negative space for page copy if needed
|
||||||
|
Lighting/mood: soft studio lighting
|
||||||
|
Constraints: no logos, no text, no watermark
|
||||||
|
```
|
||||||
|
|
||||||
|
### Edit example (invariants)
|
||||||
|
```text
|
||||||
|
Use case: precise-object-edit
|
||||||
|
Asset type: product photo background replacement
|
||||||
|
Primary request: replace only the background with a warm sunset gradient
|
||||||
|
Constraints: change only the background; keep the product and its edges unchanged; no text; no watermark
|
||||||
|
```
|
||||||
|
|
||||||
|
## Prompting best practices
|
||||||
|
- Structure prompt as scene/backdrop -> subject -> details -> constraints.
|
||||||
|
- Include intended use (ad, UI mock, infographic) to set the mode and polish level.
|
||||||
|
- Use camera/composition language for photorealism.
|
||||||
|
- Only use SVG/vector stand-ins when the user explicitly asked for vector output or a non-image placeholder.
|
||||||
|
- Quote exact text and specify typography + placement.
|
||||||
|
- For tricky words, spell them letter-by-letter and require verbatim rendering.
|
||||||
|
- For multi-image inputs, reference images by index and describe how they should be used.
|
||||||
|
- For edits, repeat invariants every iteration to reduce drift.
|
||||||
|
- Iterate with single-change follow-ups.
|
||||||
|
- If the prompt is generic, add only the extra detail that will materially help.
|
||||||
|
- If the prompt is already detailed, normalize it instead of expanding it.
|
||||||
|
- For CLI fallback only, see `references/cli.md` and `references/image-api.md` for model, `quality`, `input_fidelity`, masks, output format, and output-path guidance.
|
||||||
|
- For transparent images, use the built-in-first chroma-key workflow unless the request is complex enough to need true CLI transparency; ask before switching to CLI `gpt-image-1.5`.
|
||||||
|
|
||||||
|
More principles shared by both modes: `references/prompting.md`.
|
||||||
|
Copy/paste specs shared by both modes: `references/sample-prompts.md`.
|
||||||
|
|
||||||
|
## Guidance by asset type
|
||||||
|
Asset-type templates (website assets, game assets, wireframes, logo) are consolidated in `references/sample-prompts.md`.
|
||||||
|
|
||||||
|
## gpt-image-2 guidance for CLI fallback
|
||||||
|
|
||||||
|
The fallback CLI defaults to `gpt-image-2`.
|
||||||
|
|
||||||
|
- Use `gpt-image-2` for new CLI/API workflows unless the request needs true model-native transparent output.
|
||||||
|
- If a transparent request may need CLI fallback, ask before using `gpt-image-1.5` unless the user already explicitly requested `gpt-image-1.5`, `scripts/image_gen.py`, or CLI fallback. Explain that the built-in chroma-key path is the default, but true transparency requires `gpt-image-1.5` because `gpt-image-2` does not support `background=transparent`.
|
||||||
|
- `gpt-image-2` always uses high fidelity for image inputs; do not set `input_fidelity` with this model.
|
||||||
|
- `gpt-image-2` supports `quality` values `low`, `medium`, `high`, and `auto`.
|
||||||
|
- Use `quality low` for fast drafts, thumbnails, and quick iterations. Use `medium`, `high`, or `auto` for final assets, dense text, diagrams, identity-sensitive edits, or high-resolution outputs.
|
||||||
|
- Square images are typically fastest to generate. Use `1024x1024` for fast square drafts.
|
||||||
|
- If the user asks for 4K-style output, use `3840x2160` for landscape or `2160x3840` for portrait.
|
||||||
|
- `gpt-image-2` size may be `auto` or `WIDTHxHEIGHT` if all constraints hold: max edge `<= 3840px`, both edges multiples of `16px`, long-to-short ratio `<= 3:1`, total pixels between `655,360` and `8,294,400`.
|
||||||
|
|
||||||
|
Popular `gpt-image-2` sizes:
|
||||||
|
- `1024x1024` square
|
||||||
|
- `1536x1024` landscape
|
||||||
|
- `1024x1536` portrait
|
||||||
|
- `2048x2048` 2K square
|
||||||
|
- `2048x1152` 2K landscape
|
||||||
|
- `3840x2160` 4K landscape
|
||||||
|
- `2160x3840` 4K portrait
|
||||||
|
- `auto`
|
||||||
|
|
||||||
|
## Fallback CLI mode only
|
||||||
|
|
||||||
|
### Temp and output conventions
|
||||||
|
These conventions apply only to the CLI fallback. They do not describe built-in `image_gen` output behavior.
|
||||||
|
- Use `tmp/imagegen/` for intermediate files (for example JSONL batches); delete them when done.
|
||||||
|
- Write final artifacts under `output/imagegen/`.
|
||||||
|
- Use `--out` or `--out-dir` to control output paths; keep filenames stable and descriptive.
|
||||||
|
|
||||||
|
### Dependencies
|
||||||
|
Prefer `uv` for dependency management in this repo.
|
||||||
|
|
||||||
|
Required Python package:
|
||||||
|
```bash
|
||||||
|
uv pip install openai
|
||||||
|
```
|
||||||
|
|
||||||
|
Required for local chroma-key removal and optional downscaling:
|
||||||
|
```bash
|
||||||
|
uv pip install pillow
|
||||||
|
```
|
||||||
|
|
||||||
|
Portability note:
|
||||||
|
- If you are using the installed skill outside this repo, install dependencies into that environment with its package manager.
|
||||||
|
- In uv-managed environments, `uv pip install ...` remains the preferred path.
|
||||||
|
|
||||||
|
### Environment
|
||||||
|
- `OPENAI_API_KEY` must be set for live API calls.
|
||||||
|
- Do not ask the user for `OPENAI_API_KEY` when using the built-in `image_gen` tool.
|
||||||
|
- Never ask the user to paste the full key in chat. Ask them to set it locally and confirm when ready.
|
||||||
|
|
||||||
|
If the key is missing, give the user these steps:
|
||||||
|
1. Create an API key in the OpenAI platform UI: https://platform.openai.com/api-keys
|
||||||
|
2. Set `OPENAI_API_KEY` as an environment variable in their system.
|
||||||
|
3. Offer to guide them through setting the environment variable for their OS/shell if needed.
|
||||||
|
|
||||||
|
If installation is not possible in this environment, tell the user which dependency is missing and how to install it into their active environment.
|
||||||
|
|
||||||
|
### Script-mode notes
|
||||||
|
- CLI commands + examples: `references/cli.md`
|
||||||
|
- API parameter quick reference: `references/image-api.md`
|
||||||
|
- Network approvals / sandbox settings for CLI mode: `references/codex-network.md`
|
||||||
|
|
||||||
|
## Reference map
|
||||||
|
- `references/prompting.md`: shared prompting principles for both modes.
|
||||||
|
- `references/sample-prompts.md`: shared copy/paste prompt recipes for both modes.
|
||||||
|
- `references/cli.md`: fallback-only CLI usage via `scripts/image_gen.py`.
|
||||||
|
- `references/image-api.md`: fallback-only API/CLI parameter reference.
|
||||||
|
- `references/codex-network.md`: fallback-only network/sandbox troubleshooting for CLI mode.
|
||||||
|
- `scripts/image_gen.py`: fallback-only CLI implementation. Do not load or use it unless the user explicitly chooses CLI mode or explicitly confirms a transparent request's true CLI transparency fallback.
|
||||||
|
- `$CODEX_HOME/skills/.system/imagegen/scripts/remove_chroma_key.py`: local post-processing helper for built-in transparent-image requests.
|
||||||
6
skills/.system/imagegen/agents/openai.yaml
Normal file
6
skills/.system/imagegen/agents/openai.yaml
Normal file
@ -0,0 +1,6 @@
|
|||||||
|
interface:
|
||||||
|
display_name: "Image Gen"
|
||||||
|
short_description: "Generate or edit images for websites, games, and more"
|
||||||
|
icon_small: "./assets/imagegen-small.svg"
|
||||||
|
icon_large: "./assets/imagegen.png"
|
||||||
|
default_prompt: "Use $imagegen to make or edit an image for this project."
|
||||||
5
skills/.system/imagegen/assets/imagegen-small.svg
Normal file
5
skills/.system/imagegen/assets/imagegen-small.svg
Normal file
@ -0,0 +1,5 @@
|
|||||||
|
<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" fill="currentColor" viewBox="0 0 16 16">
|
||||||
|
<path fill="currentColor" d="M7.51 6.827a1 1 0 1 1 .278 1.982 1 1 0 0 1-.278-1.982Z"/>
|
||||||
|
<path fill="currentColor" fill-rule="evenodd" d="M8.31 4.47c.368-.016.699.008 1.016.124l.186.075c.423.194.786.5 1.047.888l.067.107c.148.253.235.533.3.848.073.354.126.797.193 1.343l.277 2.25.088.745c.024.224.041.425.049.605.013.322-.004.615-.085.896l-.04.12a2.53 2.53 0 0 1-.802 1.115l-.16.118c-.281.189-.596.292-.956.366a9.46 9.46 0 0 1-.6.1l-.743.094-2.25.277c-.547.067-.99.121-1.35.136a2.765 2.765 0 0 1-.896-.085l-.12-.039a2.533 2.533 0 0 1-1.115-.802l-.118-.161c-.189-.28-.292-.596-.366-.956a9.42 9.42 0 0 1-.1-.599l-.094-.744-.276-2.25a17.884 17.884 0 0 1-.137-1.35c-.015-.367.009-.698.124-1.015l.076-.185c.193-.423.5-.787.887-1.048l.107-.067c.253-.148.534-.234.849-.3.354-.073.796-.126 1.343-.193l2.25-.277.744-.088c.224-.024.425-.041.606-.049Zm-2.905 5.978a1.47 1.47 0 0 0-.875.074c-.127.052-.267.146-.475.344-.212.204-.462.484-.822.889l-.314.351c.018.115.036.219.055.313.061.295.127.458.206.575l.07.094c.167.211.39.372.645.465l.109.032c.119.027.273.038.499.029.308-.013.7-.06 1.264-.13l2.25-.275.727-.093.198-.03-2.05-1.64a16.848 16.848 0 0 0-.96-.738c-.18-.121-.31-.19-.421-.23l-.106-.03Zm2.95-4.915c-.154.006-.33.021-.536.043l-.729.086-2.25.276c-.564.07-.956.118-1.257.18a1.937 1.937 0 0 0-.478.15l-.097.057a1.47 1.47 0 0 0-.515.608l-.044.107c-.048.133-.073.307-.06.608.012.307.06.7.129 1.264l.22 1.8.178-.197c.145-.159.278-.298.403-.418.255-.243.507-.437.809-.56l.181-.067a2.526 2.526 0 0 1 1.328-.06l.118.029c.27.079.517.215.772.387.287.194.619.46 1.03.789l2.52 2.016c.146-.148.26-.326.332-.524l.031-.109c.027-.119.039-.273.03-.499a8.311 8.311 0 0 0-.044-.536l-.086-.728-.276-2.25c-.07-.564-.118-.956-.18-1.258a1.935 1.935 0 0 0-.15-.477l-.057-.098a1.468 1.468 0 0 0-.608-.515l-.107-.043c-.133-.049-.306-.074-.607-.061Z" clip-rule="evenodd"/>
|
||||||
|
<path fill="currentColor" d="M7.783 1.272c.36.014.803.07 1.35.136l2.25.277.743.095c.224.03.423.062.6.099.36.074.675.177.955.366l.161.118c.364.29.642.675.802 1.115l.04.12c.081.28.098.574.085.896a9.42 9.42 0 0 1-.05.605l-.087.745-.277 2.25c-.067.547-.12.989-.193 1.343a2.765 2.765 0 0 1-.3.848l-.067.107a2.534 2.534 0 0 1-.415.474l-.086.064a.532.532 0 0 1-.622-.858l.13-.13c.04-.046.077-.094.111-.145l.057-.098c.055-.109.104-.256.15-.477.062-.302.11-.694.18-1.258l.276-2.25.086-.728c.022-.207.037-.382.043-.536.01-.226-.002-.38-.029-.5l-.032-.108a1.469 1.469 0 0 0-.464-.646l-.094-.069c-.118-.08-.28-.145-.575-.206a8.285 8.285 0 0 0-.53-.088l-.728-.092-2.25-.276c-.565-.07-.956-.117-1.264-.13a1.94 1.94 0 0 0-.5.029l-.108.032a1.469 1.469 0 0 0-.647.465l-.068.094c-.054.08-.102.18-.146.33l-.04.1a.533.533 0 0 1-.98-.403l.055-.166c.059-.162.133-.314.23-.457l.117-.16c.29-.365.675-.643 1.115-.803l.12-.04c.28-.08.574-.097.896-.084Z"/>
|
||||||
|
</svg>
|
||||||
|
After Width: | Height: | Size: 2.8 KiB |
BIN
skills/.system/imagegen/assets/imagegen.png
Normal file
BIN
skills/.system/imagegen/assets/imagegen.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 1.7 KiB |
242
skills/.system/imagegen/references/cli.md
Normal file
242
skills/.system/imagegen/references/cli.md
Normal file
@ -0,0 +1,242 @@
|
|||||||
|
# CLI reference (`scripts/image_gen.py`)
|
||||||
|
|
||||||
|
This file is for the fallback CLI mode only. Read it when the user explicitly asks to use `scripts/image_gen.py` / CLI / API / model controls, or after the user explicitly confirms that a transparent-output request should use the `gpt-image-1.5` true-transparency fallback path.
|
||||||
|
|
||||||
|
`generate-batch` is a CLI subcommand in this fallback path. It is not a top-level mode of the skill.
|
||||||
|
The word `batch` in a user request is not CLI opt-in by itself.
|
||||||
|
|
||||||
|
## What this CLI does
|
||||||
|
- `generate`: generate a new image from a prompt
|
||||||
|
- `edit`: edit one or more existing images
|
||||||
|
- `generate-batch`: run many generation jobs from a JSONL file after the user explicitly chooses CLI/API/model controls
|
||||||
|
|
||||||
|
Real API calls require **network access** + `OPENAI_API_KEY`. `--dry-run` does not.
|
||||||
|
|
||||||
|
## Quick start (works from any repo)
|
||||||
|
Set a stable path to the skill CLI (default `CODEX_HOME` is `~/.codex`):
|
||||||
|
|
||||||
|
```
|
||||||
|
export CODEX_HOME="${CODEX_HOME:-$HOME/.codex}"
|
||||||
|
export IMAGE_GEN="$CODEX_HOME/skills/.system/imagegen/scripts/image_gen.py"
|
||||||
|
```
|
||||||
|
|
||||||
|
Install dependencies into that environment with its package manager. In uv-managed environments, `uv pip install ...` remains the preferred path.
|
||||||
|
|
||||||
|
## Quick start
|
||||||
|
|
||||||
|
Dry-run (no API call; no network required; does not require the `openai` package):
|
||||||
|
|
||||||
|
```bash
|
||||||
|
python "$IMAGE_GEN" generate \
|
||||||
|
--prompt "Test" \
|
||||||
|
--out output/imagegen/test.png \
|
||||||
|
--dry-run
|
||||||
|
```
|
||||||
|
|
||||||
|
Notes:
|
||||||
|
- One-off dry-runs print the API payload and the computed output path(s).
|
||||||
|
- Repo-local finals should live under `output/imagegen/`.
|
||||||
|
|
||||||
|
Generate (requires `OPENAI_API_KEY` + network):
|
||||||
|
|
||||||
|
```bash
|
||||||
|
python "$IMAGE_GEN" generate \
|
||||||
|
--prompt "A cozy alpine cabin at dawn" \
|
||||||
|
--size 1024x1024 \
|
||||||
|
--out output/imagegen/alpine-cabin.png
|
||||||
|
```
|
||||||
|
|
||||||
|
Edit:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
python "$IMAGE_GEN" edit \
|
||||||
|
--image input.png \
|
||||||
|
--prompt "Replace only the background with a warm sunset" \
|
||||||
|
--out output/imagegen/sunset-edit.png
|
||||||
|
```
|
||||||
|
|
||||||
|
## Guardrails
|
||||||
|
- Use the bundled CLI directly (`python "$IMAGE_GEN" ...`) after activating the correct environment.
|
||||||
|
- Do **not** create one-off runners (for example `gen_images.py`) unless the user explicitly asks for a custom wrapper.
|
||||||
|
- **Never modify** `scripts/image_gen.py`. If something is missing, ask the user before doing anything else.
|
||||||
|
- Do not silently downgrade from CLI `gpt-image-2` or built-in `image_gen` to CLI `gpt-image-1.5`; ask first unless the user already explicitly requested `gpt-image-1.5`, `scripts/image_gen.py`, or CLI fallback.
|
||||||
|
|
||||||
|
## Defaults
|
||||||
|
- Model: `gpt-image-2`
|
||||||
|
- Supported model family for this CLI: GPT Image models (`gpt-image-*`)
|
||||||
|
- Size: `auto`
|
||||||
|
- Quality: `medium`
|
||||||
|
- Output format: `png`
|
||||||
|
- Default one-off output path: `output/imagegen/output.png`
|
||||||
|
- Background: unspecified unless `--background` is set
|
||||||
|
|
||||||
|
## gpt-image-2 size and model guidance
|
||||||
|
|
||||||
|
`gpt-image-2` is the default model for new CLI fallback work.
|
||||||
|
|
||||||
|
- Use `--quality low` for fast drafts, thumbnails, and quick iterations.
|
||||||
|
- Use `--quality medium`, `--quality high`, or `--quality auto` for final assets, dense text, diagrams, identity-sensitive edits, and high-resolution outputs.
|
||||||
|
- Square images are typically fastest. Use `--size 1024x1024` for quick square drafts.
|
||||||
|
- If the user asks for 4K-style output, use `--size 3840x2160` for landscape or `--size 2160x3840` for portrait.
|
||||||
|
- Do not pass `--input-fidelity` with `gpt-image-2`; this model always uses high fidelity for image inputs.
|
||||||
|
- Do not use `--background transparent` with `gpt-image-2`; the default transparent-image workflow uses built-in `image_gen` on a flat chroma-key background plus local removal. Use `gpt-image-1.5` only after the user explicitly confirms the true-transparent CLI fallback, unless they already requested `gpt-image-1.5`, `scripts/image_gen.py`, or CLI fallback.
|
||||||
|
|
||||||
|
Popular `gpt-image-2` sizes:
|
||||||
|
- `1024x1024`
|
||||||
|
- `1536x1024`
|
||||||
|
- `1024x1536`
|
||||||
|
- `2048x2048`
|
||||||
|
- `2048x1152`
|
||||||
|
- `3840x2160`
|
||||||
|
- `2160x3840`
|
||||||
|
- `auto`
|
||||||
|
|
||||||
|
`gpt-image-2` size constraints:
|
||||||
|
- max edge `<= 3840px`
|
||||||
|
- both edges multiples of `16px`
|
||||||
|
- long edge to short edge ratio `<= 3:1`
|
||||||
|
- total pixels between `655,360` and `8,294,400`
|
||||||
|
- outputs above `2560x1440` total pixels are experimental
|
||||||
|
|
||||||
|
Fast draft:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
python "$IMAGE_GEN" generate \
|
||||||
|
--prompt "A product thumbnail of a matte ceramic mug on a stone surface" \
|
||||||
|
--quality low \
|
||||||
|
--size 1024x1024 \
|
||||||
|
--out output/imagegen/mug-draft.png
|
||||||
|
```
|
||||||
|
|
||||||
|
Final 2K landscape:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
python "$IMAGE_GEN" generate \
|
||||||
|
--prompt "A polished landing-page hero image of a matte ceramic mug on a stone surface" \
|
||||||
|
--quality high \
|
||||||
|
--size 2048x1152 \
|
||||||
|
--out output/imagegen/mug-hero.png
|
||||||
|
```
|
||||||
|
|
||||||
|
4K landscape:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
python "$IMAGE_GEN" generate \
|
||||||
|
--prompt "A detailed architectural visualization at golden hour" \
|
||||||
|
--size 3840x2160 \
|
||||||
|
--quality high \
|
||||||
|
--out output/imagegen/architecture-4k.png
|
||||||
|
```
|
||||||
|
|
||||||
|
True transparent fallback request:
|
||||||
|
|
||||||
|
Ask for confirmation before using this command unless the user already explicitly requested `gpt-image-1.5`, `scripts/image_gen.py`, or CLI fallback.
|
||||||
|
|
||||||
|
```bash
|
||||||
|
python "$IMAGE_GEN" generate \
|
||||||
|
--model gpt-image-1.5 \
|
||||||
|
--prompt "A clean product cutout on a transparent background" \
|
||||||
|
--background transparent \
|
||||||
|
--output-format png \
|
||||||
|
--out output/imagegen/product-cutout.png
|
||||||
|
```
|
||||||
|
|
||||||
|
When using this path, explain briefly that built-in `image_gen` plus chroma-key removal is the default transparent-image path, but this request needs true model-native transparency. `gpt-image-2` does not support `background=transparent`, so `gpt-image-1.5` is required for this confirmed fallback.
|
||||||
|
|
||||||
|
## Quality, input fidelity, and masks (CLI fallback only)
|
||||||
|
These are explicit CLI controls. They are not built-in `image_gen` tool arguments.
|
||||||
|
|
||||||
|
- `--quality` works for `generate`, `edit`, and `generate-batch`: `low|medium|high|auto`
|
||||||
|
- `--input-fidelity` is **edit-only** and validated as `low|high`; it is not supported for `gpt-image-2`
|
||||||
|
- `--mask` is **edit-only**
|
||||||
|
|
||||||
|
Example:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
python "$IMAGE_GEN" edit \
|
||||||
|
--model gpt-image-1.5 \
|
||||||
|
--image input.png \
|
||||||
|
--prompt "Change only the background" \
|
||||||
|
--quality high \
|
||||||
|
--input-fidelity high \
|
||||||
|
--out output/imagegen/background-edit.png
|
||||||
|
```
|
||||||
|
|
||||||
|
Mask notes:
|
||||||
|
- For multi-image edits, pass repeated `--image` flags. Their order is meaningful, so describe each image by index and role in the prompt.
|
||||||
|
- The CLI accepts a single `--mask`.
|
||||||
|
- Image and mask must be the same size and format and each under 50MB.
|
||||||
|
- Masks must include an alpha channel.
|
||||||
|
- If multiple input images are provided, the mask applies to the first image.
|
||||||
|
- Masking is prompt-guided; do not promise exact pixel-perfect mask boundaries.
|
||||||
|
- Use a PNG mask when possible; the script treats mask handling as best-effort and does not perform full preflight validation beyond file checks/warnings.
|
||||||
|
- In the edit prompt, repeat invariants (`change only the background; keep the subject unchanged`) to reduce drift.
|
||||||
|
|
||||||
|
## Output handling
|
||||||
|
- Use `tmp/imagegen/` for temporary JSONL inputs or scratch files.
|
||||||
|
- Use `output/imagegen/` for final outputs.
|
||||||
|
- Reruns fail if a target file already exists unless you pass `--force`.
|
||||||
|
- `--out-dir` changes one-off naming to `image_1.<ext>`, `image_2.<ext>`, and so on.
|
||||||
|
- Downscaled copies use the default suffix `-web` unless you override it.
|
||||||
|
|
||||||
|
## Common recipes
|
||||||
|
|
||||||
|
Generate with augmentation fields:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
python "$IMAGE_GEN" generate \
|
||||||
|
--prompt "A minimal hero image of a ceramic coffee mug" \
|
||||||
|
--use-case "product-mockup" \
|
||||||
|
--style "clean product photography" \
|
||||||
|
--composition "wide product shot with usable negative space for page copy" \
|
||||||
|
--constraints "no logos, no text" \
|
||||||
|
--out output/imagegen/mug-hero.png
|
||||||
|
```
|
||||||
|
|
||||||
|
Generate + also write a downscaled copy for fast web loading:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
python "$IMAGE_GEN" generate \
|
||||||
|
--prompt "A cozy alpine cabin at dawn" \
|
||||||
|
--size 1024x1024 \
|
||||||
|
--downscale-max-dim 1024 \
|
||||||
|
--out output/imagegen/alpine-cabin.png
|
||||||
|
```
|
||||||
|
|
||||||
|
Generate multiple prompts concurrently (async batch):
|
||||||
|
|
||||||
|
```bash
|
||||||
|
mkdir -p tmp/imagegen output/imagegen/batch
|
||||||
|
cat > tmp/imagegen/prompts.jsonl << 'EOF'
|
||||||
|
{"prompt":"Cavernous hangar interior with a compact shuttle parked near the center","use_case":"stylized-concept","composition":"wide-angle, low-angle","lighting":"volumetric light rays through drifting fog","constraints":"no logos or trademarks; no watermark","size":"1536x1024"}
|
||||||
|
{"prompt":"Gray wolf in profile in a snowy forest","use_case":"photorealistic-natural","composition":"eye-level","constraints":"no logos or trademarks; no watermark","size":"1024x1024"}
|
||||||
|
EOF
|
||||||
|
|
||||||
|
python "$IMAGE_GEN" generate-batch \
|
||||||
|
--input tmp/imagegen/prompts.jsonl \
|
||||||
|
--out-dir output/imagegen/batch \
|
||||||
|
--concurrency 5
|
||||||
|
|
||||||
|
rm -f tmp/imagegen/prompts.jsonl
|
||||||
|
```
|
||||||
|
|
||||||
|
Notes:
|
||||||
|
- `generate-batch` requires `--out-dir`.
|
||||||
|
- generate-batch requires --out-dir.
|
||||||
|
- Use `--concurrency` to control parallelism (default `5`).
|
||||||
|
- Per-job overrides are supported in JSONL (for example `size`, `quality`, `background`, `output_format`, `output_compression`, `moderation`, `n`, `model`, `out`, and prompt-augmentation fields).
|
||||||
|
- `--n` generates multiple variants for a single prompt; `generate-batch` is for many different prompts.
|
||||||
|
- In batch mode, per-job `out` is treated as a filename under `--out-dir`.
|
||||||
|
- For many requested deliverable assets, provide one prompt/job per distinct asset and use semantic filenames when possible.
|
||||||
|
|
||||||
|
## CLI notes
|
||||||
|
- Supported sizes depend on the model. `gpt-image-2` supports flexible constrained sizes; older GPT Image models support `1024x1024`, `1536x1024`, `1024x1536`, or `auto`.
|
||||||
|
- True transparent CLI outputs require `output_format` to be `png` or `webp` and are not supported by `gpt-image-2`.
|
||||||
|
- `--prompt-file`, `--output-compression`, `--moderation`, `--max-attempts`, `--fail-fast`, `--force`, and `--no-augment` are supported.
|
||||||
|
- This CLI is intended for GPT Image models. Do not assume older non-GPT image-model behavior applies here.
|
||||||
|
|
||||||
|
## See also
|
||||||
|
- API parameter quick reference for fallback CLI mode: `references/image-api.md`
|
||||||
|
- Prompt examples shared across both top-level modes: `references/sample-prompts.md`
|
||||||
|
- Network/sandbox notes for fallback CLI mode: `references/codex-network.md`
|
||||||
|
- Built-in-first transparent image workflow: `SKILL.md` and `$CODEX_HOME/skills/.system/imagegen/scripts/remove_chroma_key.py`
|
||||||
33
skills/.system/imagegen/references/codex-network.md
Normal file
33
skills/.system/imagegen/references/codex-network.md
Normal file
@ -0,0 +1,33 @@
|
|||||||
|
# Codex network approvals / sandbox notes
|
||||||
|
|
||||||
|
This file is for the fallback CLI mode only. Read it when the user explicitly asks to use `scripts/image_gen.py` / CLI / API / model controls, or after the user explicitly confirms that a transparent-output request should use the `gpt-image-1.5` true-transparency fallback path.
|
||||||
|
|
||||||
|
This guidance is intentionally isolated from `SKILL.md` because it can vary by environment and may become stale. Prefer the defaults in your environment when in doubt.
|
||||||
|
|
||||||
|
## Why am I asked to approve image generation calls?
|
||||||
|
The fallback CLI uses the OpenAI Image API, so it needs outbound network access. In many Codex setups, network access is disabled by default and/or the approval policy requires confirmation before networked commands run.
|
||||||
|
|
||||||
|
## Important note about approvals vs network
|
||||||
|
- `--ask-for-approval never` suppresses approval prompts.
|
||||||
|
- It does **not** by itself enable network access.
|
||||||
|
- In `workspace-write`, network access still depends on your Codex configuration (for example `[sandbox_workspace_write] network_access = true`).
|
||||||
|
|
||||||
|
## How do I reduce repeated approval prompts?
|
||||||
|
If you trust the repo and want fewer prompts, use a configuration or profile that both:
|
||||||
|
- enables network for the sandbox mode you plan to use
|
||||||
|
- sets an approval policy that matches your risk tolerance
|
||||||
|
|
||||||
|
Example `~/.codex/config.toml` pattern:
|
||||||
|
|
||||||
|
```toml
|
||||||
|
approval_policy = "on-request"
|
||||||
|
sandbox_mode = "workspace-write"
|
||||||
|
|
||||||
|
[sandbox_workspace_write]
|
||||||
|
network_access = true
|
||||||
|
```
|
||||||
|
|
||||||
|
If you want quieter automation after network is enabled, you can choose a stricter approval policy, but do that intentionally and with care.
|
||||||
|
|
||||||
|
## Safety note
|
||||||
|
Enabling network and reducing approvals lowers friction, but increases risk if you run untrusted code or work in an untrusted repository.
|
||||||
90
skills/.system/imagegen/references/image-api.md
Normal file
90
skills/.system/imagegen/references/image-api.md
Normal file
@ -0,0 +1,90 @@
|
|||||||
|
# Image API quick reference
|
||||||
|
|
||||||
|
This file is for the fallback CLI mode only. Use it when the user explicitly asks to use `scripts/image_gen.py` / CLI / API / model controls, or after the user explicitly confirms that a transparent-output request should use the `gpt-image-1.5` true-transparency fallback path.
|
||||||
|
|
||||||
|
These parameters describe the Image API and bundled CLI fallback surface. Do not assume they are normal arguments on the built-in `image_gen` tool.
|
||||||
|
|
||||||
|
## Scope
|
||||||
|
- This fallback CLI is intended for GPT Image models (`gpt-image-2`, `gpt-image-1.5`, `gpt-image-1`, and `gpt-image-1-mini`).
|
||||||
|
- The built-in `image_gen` tool and the fallback CLI do not expose the same controls.
|
||||||
|
|
||||||
|
## Model summary
|
||||||
|
|
||||||
|
| Model | Quality | Input fidelity | Resolutions | Recommended use |
|
||||||
|
| --- | --- | --- | --- | --- |
|
||||||
|
| `gpt-image-2` | `low`, `medium`, `high`, `auto` | Always high fidelity for image inputs; do not set `input_fidelity` | `auto` or flexible sizes that satisfy the constraints below | Default for new CLI/API workflows: high-quality generation and editing, text-heavy images, photorealism, compositing, identity-sensitive edits, and workflows where fewer retries matter |
|
||||||
|
| `gpt-image-1.5` | `low`, `medium`, `high`, `auto` | `low`, `high` | `1024x1024`, `1024x1536`, `1536x1024`, `auto` | True transparent-background fallback and backward-compatible workflows |
|
||||||
|
| `gpt-image-1` | `low`, `medium`, `high`, `auto` | `low`, `high` | `1024x1024`, `1024x1536`, `1536x1024`, `auto` | Legacy compatibility |
|
||||||
|
| `gpt-image-1-mini` | `low`, `medium`, `high`, `auto` | `low`, `high` | `1024x1024`, `1024x1536`, `1536x1024`, `auto` | Cost-sensitive draft batches and lower-stakes previews |
|
||||||
|
|
||||||
|
## gpt-image-2 sizes
|
||||||
|
|
||||||
|
`gpt-image-2` accepts `auto` or any `WIDTHxHEIGHT` size that satisfies all constraints:
|
||||||
|
|
||||||
|
- Maximum edge length must be less than or equal to `3840px`.
|
||||||
|
- Both edges must be multiples of `16px`.
|
||||||
|
- Long edge to short edge ratio must not exceed `3:1`.
|
||||||
|
- Total pixels must be at least `655,360` and no more than `8,294,400`.
|
||||||
|
|
||||||
|
Popular sizes:
|
||||||
|
|
||||||
|
| Label | Size | Notes |
|
||||||
|
| --- | --- | --- |
|
||||||
|
| Square | `1024x1024` | Typical fast default |
|
||||||
|
| Landscape | `1536x1024` | Standard landscape |
|
||||||
|
| Portrait | `1024x1536` | Standard portrait |
|
||||||
|
| 2K square | `2048x2048` | Larger square output |
|
||||||
|
| 2K landscape | `2048x1152` | Widescreen output |
|
||||||
|
| 4K landscape | `3840x2160` | Widescreen 4K output |
|
||||||
|
| 4K portrait | `2160x3840` | Vertical 4K output |
|
||||||
|
| Auto | `auto` | Default size |
|
||||||
|
|
||||||
|
Square images are typically fastest to generate. For 4K-style output, use `3840x2160` or `2160x3840`.
|
||||||
|
|
||||||
|
## Endpoints
|
||||||
|
- Generate: `POST /v1/images/generations` (`client.images.generate(...)`)
|
||||||
|
- Edit: `POST /v1/images/edits` (`client.images.edit(...)`)
|
||||||
|
|
||||||
|
## Core parameters for GPT Image models
|
||||||
|
- `prompt`: text prompt
|
||||||
|
- `model`: image model
|
||||||
|
- `n`: number of images (1-10)
|
||||||
|
- `size`: `auto` by default for `gpt-image-2`; flexible `WIDTHxHEIGHT` sizes are allowed only for `gpt-image-2`; older GPT Image models use `1024x1024`, `1536x1024`, `1024x1536`, or `auto`
|
||||||
|
- `quality`: `low`, `medium`, `high`, or `auto`
|
||||||
|
- `background`: output transparency behavior (`transparent`, `opaque`, or `auto`) for generated output; this is not the same thing as the prompt's visual scene/backdrop
|
||||||
|
- `output_format`: `png` (default), `jpeg`, `webp`
|
||||||
|
- `output_compression`: 0-100 (jpeg/webp only)
|
||||||
|
- `moderation`: `auto` (default) or `low`
|
||||||
|
|
||||||
|
## Edit-specific parameters
|
||||||
|
- `image`: one or more input images. For GPT Image models, you can provide up to 16 images.
|
||||||
|
- `mask`: optional mask image
|
||||||
|
- `input_fidelity`: `low` or `high` only for models that support it; do not set this for `gpt-image-2`
|
||||||
|
|
||||||
|
Model-specific note for `input_fidelity`:
|
||||||
|
- `gpt-image-2` always uses high fidelity for image inputs and does not support setting `input_fidelity`.
|
||||||
|
- `gpt-image-1` and `gpt-image-1-mini` preserve all input images, but the first image gets richer textures and finer details.
|
||||||
|
- `gpt-image-1.5` preserves the first 5 input images with higher fidelity.
|
||||||
|
|
||||||
|
## Transparent backgrounds
|
||||||
|
|
||||||
|
`gpt-image-2` does not currently support the Image API `background=transparent` parameter. The skill's default transparent-image path is built-in `image_gen` with a flat chroma-key background, followed by local alpha extraction with `python "${CODEX_HOME:-$HOME/.codex}/skills/.system/imagegen/scripts/remove_chroma_key.py"`.
|
||||||
|
|
||||||
|
Use CLI `gpt-image-1.5` with `background=transparent` and a transparent-capable output format such as `png` or `webp` only after the user explicitly confirms that fallback, unless they already requested `gpt-image-1.5`, `scripts/image_gen.py`, or CLI fallback. If the user asks for true/native transparency, the subject is too complex for clean chroma-key removal, or local background removal fails validation, explain the tradeoff and ask before switching.
|
||||||
|
|
||||||
|
## Output
|
||||||
|
- `data[]` list with `b64_json` per image
|
||||||
|
- The bundled `scripts/image_gen.py` CLI decodes `b64_json` and writes output files for you.
|
||||||
|
|
||||||
|
## Limits and notes
|
||||||
|
- Input images and masks must be under 50MB.
|
||||||
|
- Use the edits endpoint when the user requests changes to an existing image.
|
||||||
|
- Masking is prompt-guided; exact shapes are not guaranteed.
|
||||||
|
- Large sizes and high quality increase latency and cost.
|
||||||
|
- Use `quality=low` for fast drafts, thumbnails, and quick iterations. Use `medium` or `high` for final assets, dense text, diagrams, identity-sensitive edits, or high-resolution outputs.
|
||||||
|
- High `input_fidelity` can materially increase input token usage on models that support it.
|
||||||
|
- If a request fails because a specific option is unsupported by the selected GPT Image model, retry manually without that option only when the option is not required by the user. If true transparent CLI output is required, ask before switching to `gpt-image-1.5` instead of dropping `background=transparent`, unless the user already explicitly chose that fallback.
|
||||||
|
|
||||||
|
## Important boundary
|
||||||
|
- `quality`, `input_fidelity`, explicit masks, `background`, `output_format`, and related parameters are fallback-only execution controls.
|
||||||
|
- Do not assume they are built-in `image_gen` tool arguments.
|
||||||
118
skills/.system/imagegen/references/prompting.md
Normal file
118
skills/.system/imagegen/references/prompting.md
Normal file
@ -0,0 +1,118 @@
|
|||||||
|
# Prompting best practices
|
||||||
|
|
||||||
|
These prompting principles are shared by both top-level modes of the skill:
|
||||||
|
- built-in `image_gen` tool (default)
|
||||||
|
- explicit `scripts/image_gen.py` CLI fallback
|
||||||
|
|
||||||
|
This file is about prompt structure, specificity, and iteration. Fallback-only execution controls such as `quality`, `input_fidelity`, masks, output format, and output paths live in the fallback docs.
|
||||||
|
|
||||||
|
## Contents
|
||||||
|
- [Structure](#structure)
|
||||||
|
- [Specificity policy](#specificity-policy)
|
||||||
|
- [Allowed and disallowed augmentation](#allowed-and-disallowed-augmentation)
|
||||||
|
- [Composition and layout](#composition-and-layout)
|
||||||
|
- [Constraints and invariants](#constraints-and-invariants)
|
||||||
|
- [Text in images](#text-in-images)
|
||||||
|
- [Input images and references](#input-images-and-references)
|
||||||
|
- [Iterate deliberately](#iterate-deliberately)
|
||||||
|
- [Transparent images](#transparent-images)
|
||||||
|
- [Fallback-only execution controls](#fallback-only-execution-controls)
|
||||||
|
- [Use-case tips](#use-case-tips)
|
||||||
|
- [Where to find copy/paste recipes](#where-to-find-copypaste-recipes)
|
||||||
|
|
||||||
|
## Structure
|
||||||
|
- Use a consistent order: scene/backdrop -> subject -> key details -> constraints -> output intent.
|
||||||
|
- Include intended use (ad, UI mock, infographic) to set the level of polish.
|
||||||
|
- For complex requests, use short labeled lines instead of one long paragraph.
|
||||||
|
|
||||||
|
## Specificity policy
|
||||||
|
- If the user prompt is already specific and detailed, normalize it into a clean spec without adding creative requirements.
|
||||||
|
- If the prompt is generic, you may add tasteful detail when it materially improves the output.
|
||||||
|
- Treat examples in `sample-prompts.md` as fully-authored recipes, not as the default amount of augmentation to add to every request.
|
||||||
|
- For photorealism, include `photorealistic` directly when that is the goal, plus concrete real-world texture such as pores, wrinkles, fabric wear, material grain, or imperfect everyday detail.
|
||||||
|
|
||||||
|
## Allowed and disallowed augmentation
|
||||||
|
|
||||||
|
Allowed augmentation for generic prompts:
|
||||||
|
- composition and framing cues
|
||||||
|
- intended-use or polish-level hints
|
||||||
|
- practical layout guidance
|
||||||
|
- reasonable scene concreteness that supports the request
|
||||||
|
|
||||||
|
Do not add:
|
||||||
|
- extra characters, props, or objects that are not implied
|
||||||
|
- brand palettes, slogans, or story beats that are not implied
|
||||||
|
- arbitrary side-specific placement unless the surrounding layout supports it
|
||||||
|
|
||||||
|
## Composition and layout
|
||||||
|
- Specify framing and viewpoint (close-up, wide, top-down) and placement only when it materially helps.
|
||||||
|
- Call out negative space if the asset clearly needs room for UI or copy.
|
||||||
|
- Avoid making left/right layout decisions unless the user or surrounding layout supports them.
|
||||||
|
- For people, describe body framing, scale, gaze, and object interactions when they matter (`full body visible`, `looking down at the book`, `hands naturally gripping the handlebars`).
|
||||||
|
|
||||||
|
## Constraints and invariants
|
||||||
|
- State what must not change (`keep background unchanged`).
|
||||||
|
- For edits, say `change only X; keep Y unchanged` and repeat invariants on every iteration to reduce drift.
|
||||||
|
|
||||||
|
## Text in images
|
||||||
|
- Put literal text in quotes or ALL CAPS and specify typography (font style, size, color, placement).
|
||||||
|
- Spell uncommon words letter-by-letter if accuracy matters.
|
||||||
|
- For in-image copy, require verbatim rendering and no extra characters.
|
||||||
|
- In CLI fallback mode, use `medium` or `high` quality for small text, dense infographics, data-heavy slides, multi-font layouts, legends, axes, and footnotes.
|
||||||
|
|
||||||
|
## Input images and references
|
||||||
|
- Do not assume that every provided image is an edit target.
|
||||||
|
- Label each image by index and role (`Image 1: edit target`, `Image 2: style reference`).
|
||||||
|
- If the user provides images for style, composition, or mood guidance and does not ask to modify them, treat the request as generation with references.
|
||||||
|
- If the user asks to preserve an existing image while changing specific parts, treat the request as an edit.
|
||||||
|
- For compositing, describe how the images interact (`place the subject from Image 2 into Image 1`).
|
||||||
|
|
||||||
|
## Iterate deliberately
|
||||||
|
- Start with a clean base prompt, then make small single-change edits.
|
||||||
|
- Re-specify critical constraints when you iterate.
|
||||||
|
- Prefer one targeted follow-up at a time over rewriting the whole prompt.
|
||||||
|
|
||||||
|
## Transparent images
|
||||||
|
- Use built-in `image_gen` first for transparent-image requests. If the subject is clearly too complex for chroma-key removal, explain the fallback and ask before switching to CLI.
|
||||||
|
- Prompt for a perfectly flat solid chroma-key background, usually `#00ff00`; use `#ff00ff` when the subject is green, and avoid key colors that appear in the subject.
|
||||||
|
- Explicitly prohibit shadows, gradients, floor planes, reflections, texture, and lighting variation in the background.
|
||||||
|
- Ask for crisp edges, generous padding, and no use of the key color inside the subject.
|
||||||
|
- After generation, remove the background locally with `python "${CODEX_HOME:-$HOME/.codex}/skills/.system/imagegen/scripts/remove_chroma_key.py" --input <source> --out <final.png> --auto-key border --soft-matte --transparent-threshold 12 --opaque-threshold 220 --despill` and validate the alpha result before shipping it.
|
||||||
|
- Use soft matte and despill for antialiased edges; hard tolerance-only removal is mainly for flat pixel-art or exact-color fixtures.
|
||||||
|
- Use CLI `gpt-image-1.5 --background transparent --output-format png` only after the user explicitly confirms the fallback, or when the user already explicitly requested `gpt-image-1.5`, `scripts/image_gen.py`, or CLI fallback. Ask first for true/native transparency requests, failed chroma-key validation, or complex transparent subjects such as hair, fur, glass, smoke, liquids, translucent materials, reflective objects, or soft shadows.
|
||||||
|
|
||||||
|
## Fallback-only execution controls
|
||||||
|
- `quality`, `input_fidelity`, explicit masks, output format, and output paths are fallback-only execution controls.
|
||||||
|
- Do not assume they are built-in `image_gen` tool arguments.
|
||||||
|
- If the user explicitly chooses CLI fallback, see `references/cli.md` and `references/image-api.md` for those controls.
|
||||||
|
- In CLI fallback mode, `gpt-image-2` is the default. It supports `quality=low|medium|high|auto`; use `low` for fast drafts and thumbnails, and move to `medium`, `high`, or `auto` for final assets.
|
||||||
|
- `gpt-image-2` always uses high fidelity for image inputs, so do not set `input_fidelity` with that model.
|
||||||
|
- If a transparent request needs true CLI transparency, ask before using `gpt-image-1.5` unless the user already explicitly chose it. Explain that built-in chroma-key removal is the default path, but `gpt-image-2` does not support `background=transparent`.
|
||||||
|
- If the user asks for 4K-style output with `gpt-image-2`, use `3840x2160` for landscape or `2160x3840` for portrait.
|
||||||
|
|
||||||
|
## Use-case tips
|
||||||
|
Generate:
|
||||||
|
- photorealistic-natural: Prompt as if a real photo is captured in the moment; use photography language (lens, lighting, framing); call for real texture; avoid over-stylized polish unless requested.
|
||||||
|
- product-mockup: Describe the product/packaging and materials; ensure clean silhouette and label clarity; if in-image text is needed, require verbatim rendering and specify typography.
|
||||||
|
- ui-mockup: Describe the target fidelity first (shippable mockup or low-fi wireframe), then focus on layout, hierarchy, and practical UI elements; avoid concept-art language.
|
||||||
|
- infographic-diagram: Define the audience and layout flow; label parts explicitly; require verbatim text; prefer higher quality in CLI mode for dense labels.
|
||||||
|
- logo-brand: Keep it simple and scalable; ask for a strong silhouette and balanced negative space; avoid decorative flourishes unless requested.
|
||||||
|
- ads-marketing: Write like a creative brief; include brand positioning, audience, desired vibe, scene, and exact tagline if text must appear.
|
||||||
|
- productivity-visual: Name the exact artifact (slide, chart, workflow diagram), define the canvas and hierarchy, provide real labels/data, and ask for readable typography and polished spacing.
|
||||||
|
- scientific-educational: Define audience, lesson objective, required labels, scientific constraints, arrows, and scan-friendly whitespace.
|
||||||
|
- illustration-story: Define panels or scene beats; keep each action concrete.
|
||||||
|
- stylized-concept: Specify style cues, material finish, and rendering approach (3D, painterly, clay) without inventing new story elements.
|
||||||
|
- historical-scene: State the location/date and required period accuracy; constrain clothing, props, and environment to match the era.
|
||||||
|
|
||||||
|
Edit:
|
||||||
|
- text-localization: Change only the text; preserve layout, typography, spacing, and hierarchy; no extra words or reflow unless needed.
|
||||||
|
- identity-preserve: Lock identity (face, body, pose, hair, expression); change only the specified elements; match lighting and shadows.
|
||||||
|
- precise-object-edit: Specify exactly what to remove/replace; preserve surrounding texture and lighting; keep everything else unchanged.
|
||||||
|
- lighting-weather: Change only environmental conditions (light, shadows, atmosphere, precipitation); keep geometry, framing, and subject identity.
|
||||||
|
- background-extraction: For simple opaque subjects, request a clean cutout on a perfectly flat chroma-key background; crisp silhouette; generous padding; no shadows; no halos; preserve label text exactly; no restyling. Ask before using true CLI transparency for complex subjects.
|
||||||
|
- style-transfer: Specify style cues to preserve (palette, texture, brushwork) and what must change; add `no extra elements` to prevent drift.
|
||||||
|
- compositing: Reference inputs by index; specify what moves where; match lighting, perspective, and scale; keep the base framing unchanged.
|
||||||
|
- sketch-to-render: Preserve layout, proportions, and perspective; choose materials and lighting that support the supplied sketch without adding new elements.
|
||||||
|
|
||||||
|
## Where to find copy/paste recipes
|
||||||
|
For copy/paste prompt specs (examples only), see `references/sample-prompts.md`. This file focuses on principles, specificity, and iteration patterns.
|
||||||
433
skills/.system/imagegen/references/sample-prompts.md
Normal file
433
skills/.system/imagegen/references/sample-prompts.md
Normal file
@ -0,0 +1,433 @@
|
|||||||
|
# Sample prompts (copy/paste)
|
||||||
|
|
||||||
|
These prompt recipes are shared across both top-level modes of the skill:
|
||||||
|
- built-in `image_gen` tool (default)
|
||||||
|
- `scripts/image_gen.py` CLI fallback for explicit CLI/API/model requests or user-confirmed true-transparent-output fallback requests
|
||||||
|
|
||||||
|
Use these as starting points. They are intentionally complete prompt recipes, not the default amount of augmentation to add to every user request.
|
||||||
|
|
||||||
|
When adapting a user's prompt:
|
||||||
|
- keep user-provided requirements
|
||||||
|
- only add detail according to the specificity policy in `SKILL.md`
|
||||||
|
- do not treat every example below as permission to invent extra story elements
|
||||||
|
|
||||||
|
The labeled lines are prompt scaffolding, not a closed schema. `Asset type` and `Input images` are prompt-only scaffolding; the CLI does not expose them as dedicated flags.
|
||||||
|
|
||||||
|
Execution details such as explicit CLI flags, `quality`, `input_fidelity`, masks, output formats, and local output paths depend on mode. Use the built-in tool by default, including simple transparent-image requests. For transparent images, prompt for a flat chroma-key background and remove it locally with `python "${CODEX_HOME:-$HOME/.codex}/skills/.system/imagegen/scripts/remove_chroma_key.py"`; only apply CLI-specific controls when the user explicitly opts into fallback mode or explicitly confirms that the transparent request should use true CLI transparency.
|
||||||
|
|
||||||
|
CLI model notes:
|
||||||
|
- `gpt-image-2` is the fallback CLI default for new workflows.
|
||||||
|
- `gpt-image-2` supports `quality` values `low`, `medium`, `high`, and `auto`.
|
||||||
|
- For 4K-style `gpt-image-2` output, use `3840x2160` or `2160x3840`.
|
||||||
|
- If transparent output needs true CLI fallback, ask before using `gpt-image-1.5` unless the user already explicitly requested `gpt-image-1.5`, `scripts/image_gen.py`, or CLI fallback. Explain that built-in chroma-key removal is the default path, but `gpt-image-2` does not support `background=transparent`.
|
||||||
|
- Do not set `input_fidelity` with `gpt-image-2`; image inputs already use high fidelity.
|
||||||
|
|
||||||
|
For prompting principles (structure, specificity, invariants, iteration), see `references/prompting.md`.
|
||||||
|
|
||||||
|
## Generate
|
||||||
|
|
||||||
|
### photorealistic-natural
|
||||||
|
```
|
||||||
|
Use case: photorealistic-natural
|
||||||
|
Primary request: candid photo of an elderly sailor on a small fishing boat adjusting a net
|
||||||
|
Scene/backdrop: coastal water with soft haze
|
||||||
|
Subject: weathered skin with wrinkles and sun texture
|
||||||
|
Style/medium: photorealistic candid photo
|
||||||
|
Composition/framing: medium close-up, eye-level
|
||||||
|
Lighting/mood: soft coastal daylight, shallow depth of field, subtle film grain
|
||||||
|
Materials/textures: real skin texture, worn fabric, salt-worn wood
|
||||||
|
Constraints: natural color balance; no heavy retouching; no glamorization; no watermark
|
||||||
|
Avoid: studio polish; staged look
|
||||||
|
```
|
||||||
|
|
||||||
|
### product-mockup
|
||||||
|
```
|
||||||
|
Use case: product-mockup
|
||||||
|
Primary request: premium product photo of a matte black shampoo bottle with a minimal label
|
||||||
|
Scene/backdrop: clean studio gradient from light gray to white
|
||||||
|
Subject: single bottle centered with subtle reflection
|
||||||
|
Style/medium: premium product photography
|
||||||
|
Composition/framing: centered, slight three-quarter angle, generous padding
|
||||||
|
Lighting/mood: softbox lighting, clean highlights, controlled shadows
|
||||||
|
Materials/textures: matte plastic, crisp label printing
|
||||||
|
Constraints: no logos or trademarks; no watermark
|
||||||
|
```
|
||||||
|
|
||||||
|
### ui-mockup
|
||||||
|
```
|
||||||
|
Use case: ui-mockup
|
||||||
|
Primary request: mobile app home screen for a local farmers market with vendors and daily specials
|
||||||
|
Asset type: mobile app screen
|
||||||
|
Style/medium: realistic product UI, not concept art
|
||||||
|
Composition/framing: clean vertical mobile layout with clear hierarchy
|
||||||
|
Constraints: practical layout, clear typography, no logos or trademarks, no watermark
|
||||||
|
```
|
||||||
|
|
||||||
|
### infographic-diagram
|
||||||
|
```
|
||||||
|
Use case: infographic-diagram
|
||||||
|
Primary request: detailed infographic of an automatic coffee machine flow
|
||||||
|
Scene/backdrop: clean, light neutral background
|
||||||
|
Subject: bean hopper -> grinder -> brew group -> boiler -> water tank -> drip tray
|
||||||
|
Style/medium: clean vector-like infographic with clear callouts and arrows
|
||||||
|
Composition/framing: vertical poster layout, top-to-bottom flow
|
||||||
|
Text (verbatim): "Bean Hopper", "Grinder", "Brew Group", "Boiler", "Water Tank", "Drip Tray"
|
||||||
|
Constraints: clear labels, strong contrast, no logos or trademarks, no watermark
|
||||||
|
```
|
||||||
|
|
||||||
|
### scientific-educational
|
||||||
|
```
|
||||||
|
Use case: scientific-educational
|
||||||
|
Primary request: biology diagram titled "Cellular Respiration at a Glance" for high school students
|
||||||
|
Scene/backdrop: clean white classroom handout background
|
||||||
|
Subject: glucose turns into energy inside a cell; include glycolysis, Krebs cycle, and electron transport chain
|
||||||
|
Style/medium: flat scientific diagram with consistent icons, arrows, and readable labels
|
||||||
|
Composition/framing: landscape slide-style layout with clear hierarchy and generous whitespace
|
||||||
|
Text (verbatim): "Cellular Respiration at a Glance", "Glucose", "Pyruvate", "ATP", "NADH", "FADH2", "CO2", "O2", "H2O"
|
||||||
|
Constraints: scientifically plausible; avoid tiny text; no extra decoration; no watermark
|
||||||
|
```
|
||||||
|
|
||||||
|
### logo-brand
|
||||||
|
```
|
||||||
|
Use case: logo-brand
|
||||||
|
Primary request: original logo for "Field & Flour", a local bakery
|
||||||
|
Style/medium: vector logo mark; flat colors; minimal
|
||||||
|
Composition/framing: single centered logo on a plain background with generous padding
|
||||||
|
Constraints: strong silhouette, balanced negative space; original design only; no gradients unless essential; no trademarks; no watermark
|
||||||
|
```
|
||||||
|
|
||||||
|
### illustration-story
|
||||||
|
```
|
||||||
|
Use case: illustration-story
|
||||||
|
Primary request: 4-panel comic about a pet left alone at home
|
||||||
|
Scene/backdrop: cozy living room across panels
|
||||||
|
Subject: pet reacting to the owner leaving, then relaxing, then returning to a composed pose
|
||||||
|
Style/medium: comic illustration with clear panels
|
||||||
|
Composition/framing: 4 equal-sized vertical panels, readable actions per panel
|
||||||
|
Constraints: no text; no logos or trademarks; no watermark
|
||||||
|
```
|
||||||
|
|
||||||
|
### stylized-concept
|
||||||
|
```
|
||||||
|
Use case: stylized-concept
|
||||||
|
Primary request: cavernous hangar interior with tall support beams and drifting fog
|
||||||
|
Scene/backdrop: industrial hangar interior, deep scale, light haze
|
||||||
|
Subject: compact shuttle parked near the center
|
||||||
|
Style/medium: cinematic concept art, industrial realism
|
||||||
|
Composition/framing: wide-angle, low-angle
|
||||||
|
Lighting/mood: volumetric light rays cutting through fog
|
||||||
|
Constraints: no logos or trademarks; no watermark
|
||||||
|
```
|
||||||
|
|
||||||
|
### ads-marketing
|
||||||
|
```
|
||||||
|
Use case: ads-marketing
|
||||||
|
Primary request: campaign image for a streetwear brand called Thread
|
||||||
|
Subject: group of friends hanging out together in a stylish urban setting
|
||||||
|
Style/medium: polished youth streetwear campaign photography
|
||||||
|
Composition/framing: vertical ad layout with natural poses and integrated headline space
|
||||||
|
Lighting/mood: contemporary, energetic, tasteful
|
||||||
|
Text (verbatim): "Yours to Create."
|
||||||
|
Constraints: render the tagline exactly once; clean legible typography; no extra text; no watermarks; no unrelated logos
|
||||||
|
```
|
||||||
|
|
||||||
|
### productivity-visual
|
||||||
|
```
|
||||||
|
Use case: productivity-visual
|
||||||
|
Primary request: one pitch-deck slide titled "Market Opportunity"
|
||||||
|
Asset type: fundraising slide image
|
||||||
|
Style/medium: clean modern deck slide, white background, crisp sans-serif typography
|
||||||
|
Subject: TAM/SAM/SOM concentric-circle diagram plus a small growth bar chart from 2021 to 2026
|
||||||
|
Composition/framing: 16:9 landscape slide, clear data hierarchy, polished spacing
|
||||||
|
Text (verbatim): "Market Opportunity", "TAM: $42B", "SAM: $8.7B", "SOM: $340M", "AGI Research, 2024", "Internal analysis"
|
||||||
|
Constraints: readable labels, no clip art, no stock photography, no decorative clutter, no watermark
|
||||||
|
```
|
||||||
|
|
||||||
|
### historical-scene
|
||||||
|
```
|
||||||
|
Use case: historical-scene
|
||||||
|
Primary request: outdoor crowd scene in Bethel, New York on August 16, 1969
|
||||||
|
Scene/backdrop: open field with period-appropriate staging
|
||||||
|
Subject: crowd in period-accurate clothing, authentic environment
|
||||||
|
Style/medium: photorealistic photo
|
||||||
|
Composition/framing: wide shot, eye-level
|
||||||
|
Constraints: period-accurate details; no modern objects; no logos or trademarks; no watermark
|
||||||
|
```
|
||||||
|
|
||||||
|
## Asset type templates (taxonomy-aligned)
|
||||||
|
|
||||||
|
### Website assets template
|
||||||
|
```
|
||||||
|
Use case: <photorealistic-natural|stylized-concept|product-mockup|infographic-diagram|ui-mockup>
|
||||||
|
Asset type: <hero image / section illustration / blog header>
|
||||||
|
Primary request: <short description>
|
||||||
|
Scene/backdrop: <environment or abstract backdrop>
|
||||||
|
Subject: <main subject>
|
||||||
|
Style/medium: <photo/illustration/3D>
|
||||||
|
Composition/framing: <wide/centered; note usable negative space only if needed>
|
||||||
|
Lighting/mood: <soft/bright/neutral>
|
||||||
|
Color palette: <brand colors or neutral>
|
||||||
|
Constraints: <no text; no logos; no watermark; leave room for UI if needed>
|
||||||
|
```
|
||||||
|
|
||||||
|
### Website assets example: minimal hero background
|
||||||
|
```
|
||||||
|
Use case: stylized-concept
|
||||||
|
Asset type: landing page hero background
|
||||||
|
Primary request: minimal abstract background with a soft gradient and subtle texture
|
||||||
|
Style/medium: matte illustration / soft-rendered abstract background
|
||||||
|
Composition/framing: wide composition with usable negative space for page copy
|
||||||
|
Lighting/mood: gentle studio glow
|
||||||
|
Color palette: restrained neutral palette
|
||||||
|
Constraints: no text; no logos; no watermark
|
||||||
|
```
|
||||||
|
|
||||||
|
### Website assets example: feature section illustration
|
||||||
|
```
|
||||||
|
Use case: stylized-concept
|
||||||
|
Asset type: feature section illustration
|
||||||
|
Primary request: simple abstract shapes suggesting connection and flow
|
||||||
|
Scene/backdrop: subtle light-gray backdrop with faint texture
|
||||||
|
Style/medium: flat illustration; soft shadows; restrained contrast
|
||||||
|
Composition/framing: centered cluster; open margins for UI
|
||||||
|
Color palette: muted neutral palette
|
||||||
|
Constraints: no text; no logos; no watermark
|
||||||
|
```
|
||||||
|
|
||||||
|
### Website assets example: blog header image
|
||||||
|
```
|
||||||
|
Use case: photorealistic-natural
|
||||||
|
Asset type: blog header image
|
||||||
|
Primary request: overhead desk scene with notebook, pen, and coffee cup
|
||||||
|
Scene/backdrop: warm wooden tabletop
|
||||||
|
Style/medium: photorealistic photo
|
||||||
|
Composition/framing: wide crop with clean room for page copy
|
||||||
|
Lighting/mood: soft morning light
|
||||||
|
Constraints: no text; no logos; no watermark
|
||||||
|
```
|
||||||
|
|
||||||
|
### Game assets template
|
||||||
|
```
|
||||||
|
Use case: stylized-concept
|
||||||
|
Asset type: <game environment concept art / game character concept / game UI icon / tileable game texture>
|
||||||
|
Primary request: <biome/scene/character/icon/material>
|
||||||
|
Scene/backdrop: <location + set dressing> (if applicable)
|
||||||
|
Subject: <main focal element(s)>
|
||||||
|
Style/medium: <realistic/stylized>; <concept art / character render / UI icon / texture>
|
||||||
|
Composition/framing: <wide/establishing/top-down>; <camera angle>; <focal point placement>
|
||||||
|
Lighting/mood: <time of day>; <mood>; <volumetric/fog/etc>
|
||||||
|
Constraints: no logos or trademarks; no watermark
|
||||||
|
```
|
||||||
|
|
||||||
|
### Game assets example: environment concept art
|
||||||
|
```
|
||||||
|
Use case: stylized-concept
|
||||||
|
Asset type: game environment concept art
|
||||||
|
Primary request: cavernous hangar interior with tall support beams and drifting fog
|
||||||
|
Scene/backdrop: industrial hangar interior, deep scale, light haze
|
||||||
|
Subject: compact shuttle parked near the center
|
||||||
|
Style/medium: cinematic concept art, industrial realism
|
||||||
|
Composition/framing: wide-angle, low-angle
|
||||||
|
Lighting/mood: volumetric light rays cutting through fog
|
||||||
|
Constraints: no logos or trademarks; no watermark
|
||||||
|
```
|
||||||
|
|
||||||
|
### Game assets example: character concept
|
||||||
|
```
|
||||||
|
Use case: stylized-concept
|
||||||
|
Asset type: game character concept
|
||||||
|
Primary request: desert scout character with layered travel gear
|
||||||
|
Subject: long coat, satchel, practical travel clothing
|
||||||
|
Style/medium: character render; stylized realism
|
||||||
|
Composition/framing: neutral hero pose on a simple backdrop
|
||||||
|
Constraints: no logos or trademarks; no watermark
|
||||||
|
```
|
||||||
|
|
||||||
|
### Game assets example: UI icon
|
||||||
|
```
|
||||||
|
Use case: stylized-concept
|
||||||
|
Asset type: game UI icon
|
||||||
|
Primary request: round shield icon with a subtle rune pattern
|
||||||
|
Style/medium: painted game UI icon
|
||||||
|
Composition/framing: centered icon; generous padding; clear silhouette
|
||||||
|
Constraints: no text; no background scene elements; no logos or trademarks; no watermark
|
||||||
|
```
|
||||||
|
|
||||||
|
### Game assets example: tileable texture
|
||||||
|
```
|
||||||
|
Use case: stylized-concept
|
||||||
|
Asset type: tileable game texture
|
||||||
|
Primary request: worn sandstone blocks
|
||||||
|
Style/medium: seamless tileable texture; PBR-ish look
|
||||||
|
Scene/backdrop: neutral lighting reference only
|
||||||
|
Constraints: seamless edges; no obvious focal elements; no text; no logos or trademarks; no watermark
|
||||||
|
```
|
||||||
|
|
||||||
|
### Wireframe template
|
||||||
|
```
|
||||||
|
Use case: ui-mockup
|
||||||
|
Asset type: website wireframe
|
||||||
|
Primary request: <page or flow to sketch>
|
||||||
|
Style/medium: low-fi grayscale wireframe
|
||||||
|
Composition/framing: <landscape or portrait to match expected device>
|
||||||
|
Subject: <sections in order; grid/columns; key labels>
|
||||||
|
Constraints: no color; no logos; no real photos; no watermark
|
||||||
|
```
|
||||||
|
|
||||||
|
### Wireframe example: homepage (desktop)
|
||||||
|
```
|
||||||
|
Use case: ui-mockup
|
||||||
|
Asset type: website wireframe
|
||||||
|
Primary request: SaaS homepage layout with clear hierarchy
|
||||||
|
Style/medium: low-fi grayscale wireframe
|
||||||
|
Subject: top nav; hero with headline and CTA; three feature cards; testimonial strip; pricing preview; footer
|
||||||
|
Composition/framing: landscape desktop layout
|
||||||
|
Constraints: label major blocks; no color; no logos; no real photos; no watermark
|
||||||
|
```
|
||||||
|
|
||||||
|
### Wireframe example: pricing page
|
||||||
|
```
|
||||||
|
Use case: ui-mockup
|
||||||
|
Asset type: website wireframe
|
||||||
|
Primary request: pricing page layout with comparison table
|
||||||
|
Style/medium: low-fi grayscale wireframe
|
||||||
|
Subject: header; plan toggle; 3 pricing cards; comparison table; FAQ accordion; footer
|
||||||
|
Composition/framing: desktop or tablet layout
|
||||||
|
Constraints: label key areas; no color; no logos; no real photos; no watermark
|
||||||
|
```
|
||||||
|
|
||||||
|
### Wireframe example: mobile onboarding flow
|
||||||
|
```
|
||||||
|
Use case: ui-mockup
|
||||||
|
Asset type: mobile onboarding wireframe
|
||||||
|
Primary request: three-screen mobile onboarding flow
|
||||||
|
Style/medium: low-fi grayscale wireframe
|
||||||
|
Subject: screen 1 headline and CTA; screen 2 feature bullets; screen 3 form fields and CTA
|
||||||
|
Composition/framing: portrait mobile layout
|
||||||
|
Constraints: label screens and blocks; no color; no logos; no real photos; no watermark
|
||||||
|
```
|
||||||
|
|
||||||
|
### Logo template
|
||||||
|
```
|
||||||
|
Use case: logo-brand
|
||||||
|
Asset type: logo concept
|
||||||
|
Primary request: <brand idea or symbol concept>
|
||||||
|
Style/medium: vector logo mark; flat colors; minimal
|
||||||
|
Composition/framing: centered mark; clear silhouette; generous margin
|
||||||
|
Color palette: <1-2 colors; high contrast>
|
||||||
|
Text (verbatim): "<exact name>" (only if needed)
|
||||||
|
Constraints: no gradients; no mockups; no 3D; no watermark
|
||||||
|
```
|
||||||
|
|
||||||
|
### Logo example: abstract symbol mark
|
||||||
|
```
|
||||||
|
Use case: logo-brand
|
||||||
|
Asset type: logo concept
|
||||||
|
Primary request: geometric leaf symbol suggesting sustainability and growth
|
||||||
|
Style/medium: vector logo mark; flat colors; minimal
|
||||||
|
Composition/framing: centered mark; clear silhouette
|
||||||
|
Color palette: deep green and off-white
|
||||||
|
Constraints: no text unless requested; no gradients; no mockups; no 3D; no watermark
|
||||||
|
```
|
||||||
|
|
||||||
|
### Logo example: monogram mark
|
||||||
|
```
|
||||||
|
Use case: logo-brand
|
||||||
|
Asset type: logo concept
|
||||||
|
Primary request: interlocking monogram of the letters "AV"
|
||||||
|
Style/medium: vector logo mark; flat colors; minimal
|
||||||
|
Composition/framing: centered mark; balanced spacing
|
||||||
|
Color palette: black on white
|
||||||
|
Constraints: no gradients; no mockups; no 3D; no watermark
|
||||||
|
```
|
||||||
|
|
||||||
|
### Logo example: wordmark
|
||||||
|
```
|
||||||
|
Use case: logo-brand
|
||||||
|
Asset type: logo concept
|
||||||
|
Primary request: clean wordmark for a modern studio
|
||||||
|
Style/medium: vector wordmark; flat colors; minimal
|
||||||
|
Text (verbatim): "Studio North"
|
||||||
|
Composition/framing: centered text; even letter spacing
|
||||||
|
Constraints: no gradients; no mockups; no 3D; no watermark
|
||||||
|
```
|
||||||
|
|
||||||
|
## Edit
|
||||||
|
|
||||||
|
### text-localization
|
||||||
|
```
|
||||||
|
Use case: text-localization
|
||||||
|
Input images: Image 1: original infographic
|
||||||
|
Primary request: replace "Bean Hopper", "Grinder", "Brew Group", "Boiler", "Water Tank", and "Drip Tray" with "Tolva", "Molino", "Grupo de infusión", "Caldera", "Depósito de agua", and "Bandeja de goteo"
|
||||||
|
Constraints: change only the text; preserve layout, typography, spacing, and hierarchy; no extra words; do not alter logos or imagery
|
||||||
|
```
|
||||||
|
|
||||||
|
### identity-preserve
|
||||||
|
```
|
||||||
|
Use case: identity-preserve
|
||||||
|
Input images: Image 1: person photo; Image 2..N: clothing references
|
||||||
|
Primary request: replace only the clothing with the provided garments
|
||||||
|
Constraints: preserve face, body shape, pose, hair, expression, and identity; match lighting and shadows; keep the background unchanged; no accessories or text
|
||||||
|
```
|
||||||
|
|
||||||
|
### precise-object-edit
|
||||||
|
```
|
||||||
|
Use case: precise-object-edit
|
||||||
|
Input images: Image 1: room photo
|
||||||
|
Primary request: replace only the white chairs with wooden chairs
|
||||||
|
Constraints: preserve camera angle, room lighting, floor shadows, and surrounding objects; keep all other aspects unchanged
|
||||||
|
```
|
||||||
|
|
||||||
|
### lighting-weather
|
||||||
|
```
|
||||||
|
Use case: lighting-weather
|
||||||
|
Input images: Image 1: original photo
|
||||||
|
Primary request: make it look like a winter evening with gentle snowfall
|
||||||
|
Constraints: preserve subject identity, geometry, camera angle, and composition; change only lighting, atmosphere, and weather
|
||||||
|
```
|
||||||
|
|
||||||
|
### background-extraction
|
||||||
|
```
|
||||||
|
Use case: background-extraction
|
||||||
|
Input images: Image 1: product photo
|
||||||
|
Primary request: isolate the product on a clean transparent background
|
||||||
|
Scene/backdrop: perfectly flat solid #00ff00 chroma-key background for local background removal
|
||||||
|
Constraints: background must be one uniform color with no shadows, gradients, texture, reflections, floor plane, or lighting variation; crisp silhouette; generous padding; no halos or fringing; preserve label text exactly; no restyling; do not use #00ff00 anywhere in the subject
|
||||||
|
```
|
||||||
|
|
||||||
|
Post-process note: after built-in generation, run `python "${CODEX_HOME:-$HOME/.codex}/skills/.system/imagegen/scripts/remove_chroma_key.py" --input <source> --out <final.png> --auto-key border --soft-matte --transparent-threshold 12 --opaque-threshold 220 --despill`. Ask before using CLI `gpt-image-1.5 --background transparent --output-format png` for true/native transparency, failed chroma-key validation, or complex subjects such as hair, fur, glass, smoke, liquids, translucent materials, reflections, or soft shadows, unless the user already explicitly requested `gpt-image-1.5`, `scripts/image_gen.py`, or CLI fallback.
|
||||||
|
|
||||||
|
### style-transfer
|
||||||
|
```
|
||||||
|
Use case: style-transfer
|
||||||
|
Input images: Image 1: style reference
|
||||||
|
Primary request: apply Image 1's visual style to a man riding a motorcycle on a plain white backdrop
|
||||||
|
Constraints: preserve palette, texture, and brushwork; no extra elements
|
||||||
|
```
|
||||||
|
|
||||||
|
### compositing
|
||||||
|
```
|
||||||
|
Use case: compositing
|
||||||
|
Input images: Image 1: base scene; Image 2: subject to insert
|
||||||
|
Primary request: place the subject from Image 2 next to the person in Image 1
|
||||||
|
Constraints: match lighting, perspective, and scale; keep the base framing unchanged; no extra elements
|
||||||
|
```
|
||||||
|
|
||||||
|
### character consistency workflow
|
||||||
|
```
|
||||||
|
Use case: identity-preserve
|
||||||
|
Input images: Image 1: previous character anchor illustration
|
||||||
|
Primary request: continue the story with the same character in a new scene and action
|
||||||
|
Scene/backdrop: snowy forest after a winter storm
|
||||||
|
Subject: same young forest hero gently helping a frightened squirrel out of a fallen tree
|
||||||
|
Style/medium: same children's book watercolor illustration style as Image 1
|
||||||
|
Constraints: do not redesign the character; preserve facial features, proportions, outfit, color palette, and personality; no text; no watermark
|
||||||
|
```
|
||||||
|
|
||||||
|
### sketch-to-render
|
||||||
|
```
|
||||||
|
Use case: sketch-to-render
|
||||||
|
Input images: Image 1: drawing
|
||||||
|
Primary request: turn the drawing into a photorealistic image
|
||||||
|
Constraints: preserve layout, proportions, and perspective; choose realistic materials and lighting; do not add new elements or text
|
||||||
|
```
|
||||||
995
skills/.system/imagegen/scripts/image_gen.py
Normal file
995
skills/.system/imagegen/scripts/image_gen.py
Normal file
@ -0,0 +1,995 @@
|
|||||||
|
#!/usr/bin/env python3
|
||||||
|
"""Fallback CLI for explicit image generation or editing with GPT Image models.
|
||||||
|
|
||||||
|
Used only when the user explicitly opts into CLI fallback mode, or when explicit
|
||||||
|
transparent output requires the `gpt-image-1.5` fallback path.
|
||||||
|
|
||||||
|
Defaults to gpt-image-2 and a structured prompt augmentation workflow.
|
||||||
|
"""
|
||||||
|
|
||||||
|
from __future__ import annotations
|
||||||
|
|
||||||
|
import argparse
|
||||||
|
import asyncio
|
||||||
|
import base64
|
||||||
|
import json
|
||||||
|
import os
|
||||||
|
from pathlib import Path
|
||||||
|
import re
|
||||||
|
import sys
|
||||||
|
import time
|
||||||
|
from typing import Any, Dict, Iterable, List, Optional, Tuple
|
||||||
|
|
||||||
|
from io import BytesIO
|
||||||
|
|
||||||
|
DEFAULT_MODEL = "gpt-image-2"
|
||||||
|
DEFAULT_SIZE = "auto"
|
||||||
|
DEFAULT_QUALITY = "medium"
|
||||||
|
DEFAULT_OUTPUT_FORMAT = "png"
|
||||||
|
DEFAULT_CONCURRENCY = 5
|
||||||
|
DEFAULT_DOWNSCALE_SUFFIX = "-web"
|
||||||
|
DEFAULT_OUTPUT_PATH = "output/imagegen/output.png"
|
||||||
|
GPT_IMAGE_MODEL_PREFIX = "gpt-image-"
|
||||||
|
|
||||||
|
ALLOWED_LEGACY_SIZES = {"1024x1024", "1536x1024", "1024x1536", "auto"}
|
||||||
|
ALLOWED_QUALITIES = {"low", "medium", "high", "auto"}
|
||||||
|
ALLOWED_BACKGROUNDS = {"transparent", "opaque", "auto", None}
|
||||||
|
ALLOWED_INPUT_FIDELITIES = {"low", "high", None}
|
||||||
|
|
||||||
|
GPT_IMAGE_2_MODEL = "gpt-image-2"
|
||||||
|
GPT_IMAGE_2_MIN_PIXELS = 655_360
|
||||||
|
GPT_IMAGE_2_MAX_PIXELS = 8_294_400
|
||||||
|
GPT_IMAGE_2_MAX_EDGE = 3840
|
||||||
|
GPT_IMAGE_2_MAX_RATIO = 3.0
|
||||||
|
|
||||||
|
MAX_IMAGE_BYTES = 50 * 1024 * 1024
|
||||||
|
MAX_BATCH_JOBS = 500
|
||||||
|
|
||||||
|
|
||||||
|
def _die(message: str, code: int = 1) -> None:
|
||||||
|
print(f"Error: {message}", file=sys.stderr)
|
||||||
|
raise SystemExit(code)
|
||||||
|
|
||||||
|
|
||||||
|
def _warn(message: str) -> None:
|
||||||
|
print(f"Warning: {message}", file=sys.stderr)
|
||||||
|
|
||||||
|
|
||||||
|
def _dependency_hint(package: str, *, upgrade: bool = False) -> str:
|
||||||
|
command = f"uv pip install {'-U ' if upgrade else ''}{package}"
|
||||||
|
return (
|
||||||
|
"Activate the repo-selected environment first, then install it with "
|
||||||
|
f"`{command}`. If this repo uses a local virtualenv, start with "
|
||||||
|
"`source .venv/bin/activate`; otherwise use this repo's configured shared fallback "
|
||||||
|
"environment. If your project declares dependencies, prefer that project's normal "
|
||||||
|
"`uv sync` flow."
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
def _ensure_api_key(dry_run: bool) -> None:
|
||||||
|
if os.getenv("OPENAI_API_KEY"):
|
||||||
|
print("OPENAI_API_KEY is set.", file=sys.stderr)
|
||||||
|
return
|
||||||
|
if dry_run:
|
||||||
|
_warn("OPENAI_API_KEY is not set; dry-run only.")
|
||||||
|
return
|
||||||
|
_die("OPENAI_API_KEY is not set. Export it before running.")
|
||||||
|
|
||||||
|
|
||||||
|
def _read_prompt(prompt: Optional[str], prompt_file: Optional[str]) -> str:
|
||||||
|
if prompt and prompt_file:
|
||||||
|
_die("Use --prompt or --prompt-file, not both.")
|
||||||
|
if prompt_file:
|
||||||
|
path = Path(prompt_file)
|
||||||
|
if not path.exists():
|
||||||
|
_die(f"Prompt file not found: {path}")
|
||||||
|
return path.read_text(encoding="utf-8").strip()
|
||||||
|
if prompt:
|
||||||
|
return prompt.strip()
|
||||||
|
_die("Missing prompt. Use --prompt or --prompt-file.")
|
||||||
|
return "" # unreachable
|
||||||
|
|
||||||
|
|
||||||
|
def _check_image_paths(paths: Iterable[str]) -> List[Path]:
|
||||||
|
resolved: List[Path] = []
|
||||||
|
for raw in paths:
|
||||||
|
path = Path(raw)
|
||||||
|
if not path.exists():
|
||||||
|
_die(f"Image file not found: {path}")
|
||||||
|
if path.stat().st_size > MAX_IMAGE_BYTES:
|
||||||
|
_warn(f"Image exceeds 50MB limit: {path}")
|
||||||
|
resolved.append(path)
|
||||||
|
return resolved
|
||||||
|
|
||||||
|
|
||||||
|
def _normalize_output_format(fmt: Optional[str]) -> str:
|
||||||
|
if not fmt:
|
||||||
|
return DEFAULT_OUTPUT_FORMAT
|
||||||
|
fmt = fmt.lower()
|
||||||
|
if fmt not in {"png", "jpeg", "jpg", "webp"}:
|
||||||
|
_die("output-format must be png, jpeg, jpg, or webp.")
|
||||||
|
return "jpeg" if fmt == "jpg" else fmt
|
||||||
|
|
||||||
|
|
||||||
|
def _parse_size(size: str) -> Optional[Tuple[int, int]]:
|
||||||
|
match = re.fullmatch(r"([1-9][0-9]*)x([1-9][0-9]*)", size)
|
||||||
|
if not match:
|
||||||
|
return None
|
||||||
|
return int(match.group(1)), int(match.group(2))
|
||||||
|
|
||||||
|
|
||||||
|
def _validate_gpt_image_2_size(size: str) -> None:
|
||||||
|
if size == "auto":
|
||||||
|
return
|
||||||
|
|
||||||
|
parsed = _parse_size(size)
|
||||||
|
if parsed is None:
|
||||||
|
_die("size must be auto or WIDTHxHEIGHT, for example 1024x1024.")
|
||||||
|
|
||||||
|
width, height = parsed
|
||||||
|
max_edge = max(width, height)
|
||||||
|
min_edge = min(width, height)
|
||||||
|
total_pixels = width * height
|
||||||
|
|
||||||
|
if max_edge > GPT_IMAGE_2_MAX_EDGE:
|
||||||
|
_die("gpt-image-2 size maximum edge length must be less than or equal to 3840px.")
|
||||||
|
if width % 16 != 0 or height % 16 != 0:
|
||||||
|
_die("gpt-image-2 size width and height must be multiples of 16px.")
|
||||||
|
if max_edge / min_edge > GPT_IMAGE_2_MAX_RATIO:
|
||||||
|
_die("gpt-image-2 size long edge to short edge ratio must not exceed 3:1.")
|
||||||
|
if total_pixels < GPT_IMAGE_2_MIN_PIXELS or total_pixels > GPT_IMAGE_2_MAX_PIXELS:
|
||||||
|
_die(
|
||||||
|
"gpt-image-2 size total pixels must be at least 655,360 and no more than 8,294,400."
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
def _validate_size(size: str, model: str) -> None:
|
||||||
|
if model == GPT_IMAGE_2_MODEL:
|
||||||
|
_validate_gpt_image_2_size(size)
|
||||||
|
return
|
||||||
|
|
||||||
|
if size not in ALLOWED_LEGACY_SIZES:
|
||||||
|
_die(
|
||||||
|
"size must be one of 1024x1024, 1536x1024, 1024x1536, or auto for this GPT Image model."
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
def _validate_quality(quality: str) -> None:
|
||||||
|
if quality not in ALLOWED_QUALITIES:
|
||||||
|
_die("quality must be one of low, medium, high, or auto.")
|
||||||
|
|
||||||
|
|
||||||
|
def _validate_background(background: Optional[str]) -> None:
|
||||||
|
if background not in ALLOWED_BACKGROUNDS:
|
||||||
|
_die("background must be one of transparent, opaque, or auto.")
|
||||||
|
|
||||||
|
|
||||||
|
def _validate_input_fidelity(input_fidelity: Optional[str]) -> None:
|
||||||
|
if input_fidelity not in ALLOWED_INPUT_FIDELITIES:
|
||||||
|
_die("input-fidelity must be one of low or high.")
|
||||||
|
|
||||||
|
|
||||||
|
def _validate_model(model: str) -> None:
|
||||||
|
if not model.startswith(GPT_IMAGE_MODEL_PREFIX):
|
||||||
|
_die(
|
||||||
|
"model must be a GPT Image model (for example gpt-image-1.5, gpt-image-1, or gpt-image-1-mini)."
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
def _validate_transparency(background: Optional[str], output_format: str) -> None:
|
||||||
|
if background == "transparent" and output_format not in {"png", "webp"}:
|
||||||
|
_die("transparent background requires output-format png or webp.")
|
||||||
|
|
||||||
|
|
||||||
|
def _validate_model_specific_options(
|
||||||
|
*,
|
||||||
|
model: str,
|
||||||
|
background: Optional[str],
|
||||||
|
input_fidelity: Optional[str] = None,
|
||||||
|
) -> None:
|
||||||
|
if model != GPT_IMAGE_2_MODEL:
|
||||||
|
return
|
||||||
|
if background == "transparent":
|
||||||
|
_die(
|
||||||
|
"transparent backgrounds are not supported in gpt-image-2, the latest model. "
|
||||||
|
"Use --model gpt-image-1.5 --background transparent --output-format png instead."
|
||||||
|
)
|
||||||
|
if input_fidelity is not None:
|
||||||
|
_die(
|
||||||
|
"input_fidelity is not supported in gpt-image-2 because image inputs always use high fidelity for this model."
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
def _validate_generate_payload(payload: Dict[str, Any]) -> None:
|
||||||
|
model = str(payload.get("model", DEFAULT_MODEL))
|
||||||
|
_validate_model(model)
|
||||||
|
n = int(payload.get("n", 1))
|
||||||
|
if n < 1 or n > 10:
|
||||||
|
_die("n must be between 1 and 10")
|
||||||
|
size = str(payload.get("size", DEFAULT_SIZE))
|
||||||
|
quality = str(payload.get("quality", DEFAULT_QUALITY))
|
||||||
|
background = payload.get("background")
|
||||||
|
_validate_size(size, model)
|
||||||
|
_validate_quality(quality)
|
||||||
|
_validate_background(background)
|
||||||
|
_validate_model_specific_options(model=model, background=background)
|
||||||
|
oc = payload.get("output_compression")
|
||||||
|
if oc is not None and not (0 <= int(oc) <= 100):
|
||||||
|
_die("output_compression must be between 0 and 100")
|
||||||
|
|
||||||
|
|
||||||
|
def _build_output_paths(
|
||||||
|
out: str,
|
||||||
|
output_format: str,
|
||||||
|
count: int,
|
||||||
|
out_dir: Optional[str],
|
||||||
|
) -> List[Path]:
|
||||||
|
ext = "." + output_format
|
||||||
|
|
||||||
|
if out_dir:
|
||||||
|
out_base = Path(out_dir)
|
||||||
|
out_base.mkdir(parents=True, exist_ok=True)
|
||||||
|
return [out_base / f"image_{i}{ext}" for i in range(1, count + 1)]
|
||||||
|
|
||||||
|
out_path = Path(out)
|
||||||
|
if out_path.exists() and out_path.is_dir():
|
||||||
|
out_path.mkdir(parents=True, exist_ok=True)
|
||||||
|
return [out_path / f"image_{i}{ext}" for i in range(1, count + 1)]
|
||||||
|
|
||||||
|
if out_path.suffix == "":
|
||||||
|
out_path = out_path.with_suffix(ext)
|
||||||
|
elif output_format and out_path.suffix.lstrip(".").lower() != output_format:
|
||||||
|
_warn(
|
||||||
|
f"Output extension {out_path.suffix} does not match output-format {output_format}."
|
||||||
|
)
|
||||||
|
|
||||||
|
if count == 1:
|
||||||
|
return [out_path]
|
||||||
|
|
||||||
|
return [
|
||||||
|
out_path.with_name(f"{out_path.stem}-{i}{out_path.suffix}")
|
||||||
|
for i in range(1, count + 1)
|
||||||
|
]
|
||||||
|
|
||||||
|
|
||||||
|
def _augment_prompt(args: argparse.Namespace, prompt: str) -> str:
|
||||||
|
fields = _fields_from_args(args)
|
||||||
|
return _augment_prompt_fields(args.augment, prompt, fields)
|
||||||
|
|
||||||
|
|
||||||
|
def _augment_prompt_fields(augment: bool, prompt: str, fields: Dict[str, Optional[str]]) -> str:
|
||||||
|
if not augment:
|
||||||
|
return prompt
|
||||||
|
|
||||||
|
sections: List[str] = []
|
||||||
|
if fields.get("use_case"):
|
||||||
|
sections.append(f"Use case: {fields['use_case']}")
|
||||||
|
sections.append(f"Primary request: {prompt}")
|
||||||
|
if fields.get("scene"):
|
||||||
|
sections.append(f"Scene/background: {fields['scene']}")
|
||||||
|
if fields.get("subject"):
|
||||||
|
sections.append(f"Subject: {fields['subject']}")
|
||||||
|
if fields.get("style"):
|
||||||
|
sections.append(f"Style/medium: {fields['style']}")
|
||||||
|
if fields.get("composition"):
|
||||||
|
sections.append(f"Composition/framing: {fields['composition']}")
|
||||||
|
if fields.get("lighting"):
|
||||||
|
sections.append(f"Lighting/mood: {fields['lighting']}")
|
||||||
|
if fields.get("palette"):
|
||||||
|
sections.append(f"Color palette: {fields['palette']}")
|
||||||
|
if fields.get("materials"):
|
||||||
|
sections.append(f"Materials/textures: {fields['materials']}")
|
||||||
|
if fields.get("text"):
|
||||||
|
sections.append(f"Text (verbatim): \"{fields['text']}\"")
|
||||||
|
if fields.get("constraints"):
|
||||||
|
sections.append(f"Constraints: {fields['constraints']}")
|
||||||
|
if fields.get("negative"):
|
||||||
|
sections.append(f"Avoid: {fields['negative']}")
|
||||||
|
|
||||||
|
return "\n".join(sections)
|
||||||
|
|
||||||
|
|
||||||
|
def _fields_from_args(args: argparse.Namespace) -> Dict[str, Optional[str]]:
|
||||||
|
return {
|
||||||
|
"use_case": getattr(args, "use_case", None),
|
||||||
|
"scene": getattr(args, "scene", None),
|
||||||
|
"subject": getattr(args, "subject", None),
|
||||||
|
"style": getattr(args, "style", None),
|
||||||
|
"composition": getattr(args, "composition", None),
|
||||||
|
"lighting": getattr(args, "lighting", None),
|
||||||
|
"palette": getattr(args, "palette", None),
|
||||||
|
"materials": getattr(args, "materials", None),
|
||||||
|
"text": getattr(args, "text", None),
|
||||||
|
"constraints": getattr(args, "constraints", None),
|
||||||
|
"negative": getattr(args, "negative", None),
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
def _print_request(payload: dict) -> None:
|
||||||
|
print(json.dumps(payload, indent=2, sort_keys=True))
|
||||||
|
|
||||||
|
|
||||||
|
def _decode_and_write(images: List[str], outputs: List[Path], force: bool) -> None:
|
||||||
|
for idx, image_b64 in enumerate(images):
|
||||||
|
if idx >= len(outputs):
|
||||||
|
break
|
||||||
|
out_path = outputs[idx]
|
||||||
|
if out_path.exists() and not force:
|
||||||
|
_die(f"Output already exists: {out_path} (use --force to overwrite)")
|
||||||
|
out_path.parent.mkdir(parents=True, exist_ok=True)
|
||||||
|
out_path.write_bytes(base64.b64decode(image_b64))
|
||||||
|
print(f"Wrote {out_path}")
|
||||||
|
|
||||||
|
|
||||||
|
def _derive_downscale_path(path: Path, suffix: str) -> Path:
|
||||||
|
if suffix and not suffix.startswith("-") and not suffix.startswith("_"):
|
||||||
|
suffix = "-" + suffix
|
||||||
|
return path.with_name(f"{path.stem}{suffix}{path.suffix}")
|
||||||
|
|
||||||
|
|
||||||
|
def _downscale_image_bytes(image_bytes: bytes, *, max_dim: int, output_format: str) -> bytes:
|
||||||
|
try:
|
||||||
|
from PIL import Image
|
||||||
|
except Exception:
|
||||||
|
_die(f"Downscaling requires Pillow. {_dependency_hint('pillow')}")
|
||||||
|
|
||||||
|
if max_dim < 1:
|
||||||
|
_die("--downscale-max-dim must be >= 1")
|
||||||
|
|
||||||
|
with Image.open(BytesIO(image_bytes)) as img:
|
||||||
|
img.load()
|
||||||
|
w, h = img.size
|
||||||
|
scale = min(1.0, float(max_dim) / float(max(w, h)))
|
||||||
|
target = (max(1, int(round(w * scale))), max(1, int(round(h * scale))))
|
||||||
|
|
||||||
|
resized = img if target == (w, h) else img.resize(target, Image.Resampling.LANCZOS)
|
||||||
|
|
||||||
|
fmt = output_format.lower()
|
||||||
|
if fmt == "jpg":
|
||||||
|
fmt = "jpeg"
|
||||||
|
|
||||||
|
if fmt == "jpeg":
|
||||||
|
if resized.mode in ("RGBA", "LA") or ("transparency" in getattr(resized, "info", {})):
|
||||||
|
bg = Image.new("RGB", resized.size, (255, 255, 255))
|
||||||
|
bg.paste(resized.convert("RGBA"), mask=resized.convert("RGBA").split()[-1])
|
||||||
|
resized = bg
|
||||||
|
else:
|
||||||
|
resized = resized.convert("RGB")
|
||||||
|
|
||||||
|
out = BytesIO()
|
||||||
|
resized.save(out, format=fmt.upper())
|
||||||
|
return out.getvalue()
|
||||||
|
|
||||||
|
|
||||||
|
def _decode_write_and_downscale(
|
||||||
|
images: List[str],
|
||||||
|
outputs: List[Path],
|
||||||
|
*,
|
||||||
|
force: bool,
|
||||||
|
downscale_max_dim: Optional[int],
|
||||||
|
downscale_suffix: str,
|
||||||
|
output_format: str,
|
||||||
|
) -> None:
|
||||||
|
for idx, image_b64 in enumerate(images):
|
||||||
|
if idx >= len(outputs):
|
||||||
|
break
|
||||||
|
out_path = outputs[idx]
|
||||||
|
if out_path.exists() and not force:
|
||||||
|
_die(f"Output already exists: {out_path} (use --force to overwrite)")
|
||||||
|
out_path.parent.mkdir(parents=True, exist_ok=True)
|
||||||
|
|
||||||
|
raw = base64.b64decode(image_b64)
|
||||||
|
out_path.write_bytes(raw)
|
||||||
|
print(f"Wrote {out_path}")
|
||||||
|
|
||||||
|
if downscale_max_dim is None:
|
||||||
|
continue
|
||||||
|
|
||||||
|
derived = _derive_downscale_path(out_path, downscale_suffix)
|
||||||
|
if derived.exists() and not force:
|
||||||
|
_die(f"Output already exists: {derived} (use --force to overwrite)")
|
||||||
|
derived.parent.mkdir(parents=True, exist_ok=True)
|
||||||
|
resized = _downscale_image_bytes(raw, max_dim=downscale_max_dim, output_format=output_format)
|
||||||
|
derived.write_bytes(resized)
|
||||||
|
print(f"Wrote {derived}")
|
||||||
|
|
||||||
|
|
||||||
|
def _create_client():
|
||||||
|
try:
|
||||||
|
from openai import OpenAI
|
||||||
|
except ImportError:
|
||||||
|
_die(f"openai SDK not installed in the active environment. {_dependency_hint('openai')}")
|
||||||
|
return OpenAI()
|
||||||
|
|
||||||
|
|
||||||
|
def _create_async_client():
|
||||||
|
try:
|
||||||
|
from openai import AsyncOpenAI
|
||||||
|
except ImportError:
|
||||||
|
try:
|
||||||
|
import openai as _openai # noqa: F401
|
||||||
|
except ImportError:
|
||||||
|
_die(
|
||||||
|
f"openai SDK not installed in the active environment. {_dependency_hint('openai')}"
|
||||||
|
)
|
||||||
|
_die(
|
||||||
|
"AsyncOpenAI not available in this openai SDK version. "
|
||||||
|
f"{_dependency_hint('openai', upgrade=True)}"
|
||||||
|
)
|
||||||
|
return AsyncOpenAI()
|
||||||
|
|
||||||
|
|
||||||
|
def _slugify(value: str) -> str:
|
||||||
|
value = value.strip().lower()
|
||||||
|
value = re.sub(r"[^a-z0-9]+", "-", value)
|
||||||
|
value = re.sub(r"-{2,}", "-", value).strip("-")
|
||||||
|
return value[:60] if value else "job"
|
||||||
|
|
||||||
|
|
||||||
|
def _normalize_job(job: Any, idx: int) -> Dict[str, Any]:
|
||||||
|
if isinstance(job, str):
|
||||||
|
prompt = job.strip()
|
||||||
|
if not prompt:
|
||||||
|
_die(f"Empty prompt at job {idx}")
|
||||||
|
return {"prompt": prompt}
|
||||||
|
if isinstance(job, dict):
|
||||||
|
if "prompt" not in job or not str(job["prompt"]).strip():
|
||||||
|
_die(f"Missing prompt for job {idx}")
|
||||||
|
return job
|
||||||
|
_die(f"Invalid job at index {idx}: expected string or object.")
|
||||||
|
return {} # unreachable
|
||||||
|
|
||||||
|
|
||||||
|
def _read_jobs_jsonl(path: str) -> List[Dict[str, Any]]:
|
||||||
|
p = Path(path)
|
||||||
|
if not p.exists():
|
||||||
|
_die(f"Input file not found: {p}")
|
||||||
|
jobs: List[Dict[str, Any]] = []
|
||||||
|
for line_no, raw in enumerate(p.read_text(encoding="utf-8").splitlines(), start=1):
|
||||||
|
line = raw.strip()
|
||||||
|
if not line or line.startswith("#"):
|
||||||
|
continue
|
||||||
|
try:
|
||||||
|
item: Any
|
||||||
|
if line.startswith("{"):
|
||||||
|
item = json.loads(line)
|
||||||
|
else:
|
||||||
|
item = line
|
||||||
|
jobs.append(_normalize_job(item, idx=line_no))
|
||||||
|
except json.JSONDecodeError as exc:
|
||||||
|
_die(f"Invalid JSON on line {line_no}: {exc}")
|
||||||
|
if not jobs:
|
||||||
|
_die("No jobs found in input file.")
|
||||||
|
if len(jobs) > MAX_BATCH_JOBS:
|
||||||
|
_die(f"Too many jobs ({len(jobs)}). Max is {MAX_BATCH_JOBS}.")
|
||||||
|
return jobs
|
||||||
|
|
||||||
|
|
||||||
|
def _merge_non_null(dst: Dict[str, Any], src: Dict[str, Any]) -> Dict[str, Any]:
|
||||||
|
merged = dict(dst)
|
||||||
|
for k, v in src.items():
|
||||||
|
if v is not None:
|
||||||
|
merged[k] = v
|
||||||
|
return merged
|
||||||
|
|
||||||
|
|
||||||
|
def _job_output_paths(
|
||||||
|
*,
|
||||||
|
out_dir: Path,
|
||||||
|
output_format: str,
|
||||||
|
idx: int,
|
||||||
|
prompt: str,
|
||||||
|
n: int,
|
||||||
|
explicit_out: Optional[str],
|
||||||
|
) -> List[Path]:
|
||||||
|
out_dir.mkdir(parents=True, exist_ok=True)
|
||||||
|
ext = "." + output_format
|
||||||
|
|
||||||
|
if explicit_out:
|
||||||
|
base = Path(explicit_out)
|
||||||
|
if base.suffix == "":
|
||||||
|
base = base.with_suffix(ext)
|
||||||
|
elif base.suffix.lstrip(".").lower() != output_format:
|
||||||
|
_warn(
|
||||||
|
f"Job {idx}: output extension {base.suffix} does not match output-format {output_format}."
|
||||||
|
)
|
||||||
|
base = out_dir / base.name
|
||||||
|
else:
|
||||||
|
slug = _slugify(prompt[:80])
|
||||||
|
base = out_dir / f"{idx:03d}-{slug}{ext}"
|
||||||
|
|
||||||
|
if n == 1:
|
||||||
|
return [base]
|
||||||
|
return [
|
||||||
|
base.with_name(f"{base.stem}-{i}{base.suffix}")
|
||||||
|
for i in range(1, n + 1)
|
||||||
|
]
|
||||||
|
|
||||||
|
|
||||||
|
def _extract_retry_after_seconds(exc: Exception) -> Optional[float]:
|
||||||
|
# Best-effort: openai SDK errors vary by version. Prefer a conservative fallback.
|
||||||
|
for attr in ("retry_after", "retry_after_seconds"):
|
||||||
|
val = getattr(exc, attr, None)
|
||||||
|
if isinstance(val, (int, float)) and val >= 0:
|
||||||
|
return float(val)
|
||||||
|
msg = str(exc)
|
||||||
|
m = re.search(r"retry[- ]after[:= ]+([0-9]+(?:\\.[0-9]+)?)", msg, re.IGNORECASE)
|
||||||
|
if m:
|
||||||
|
try:
|
||||||
|
return float(m.group(1))
|
||||||
|
except Exception:
|
||||||
|
return None
|
||||||
|
return None
|
||||||
|
|
||||||
|
|
||||||
|
def _is_rate_limit_error(exc: Exception) -> bool:
|
||||||
|
name = exc.__class__.__name__.lower()
|
||||||
|
if "ratelimit" in name or "rate_limit" in name:
|
||||||
|
return True
|
||||||
|
msg = str(exc).lower()
|
||||||
|
return "429" in msg or "rate limit" in msg or "too many requests" in msg
|
||||||
|
|
||||||
|
|
||||||
|
def _is_transient_error(exc: Exception) -> bool:
|
||||||
|
if _is_rate_limit_error(exc):
|
||||||
|
return True
|
||||||
|
name = exc.__class__.__name__.lower()
|
||||||
|
if "timeout" in name or "timedout" in name or "tempor" in name:
|
||||||
|
return True
|
||||||
|
msg = str(exc).lower()
|
||||||
|
return "timeout" in msg or "timed out" in msg or "connection reset" in msg
|
||||||
|
|
||||||
|
|
||||||
|
async def _generate_one_with_retries(
|
||||||
|
client: Any,
|
||||||
|
payload: Dict[str, Any],
|
||||||
|
*,
|
||||||
|
attempts: int,
|
||||||
|
job_label: str,
|
||||||
|
) -> Any:
|
||||||
|
last_exc: Optional[Exception] = None
|
||||||
|
for attempt in range(1, attempts + 1):
|
||||||
|
try:
|
||||||
|
return await client.images.generate(**payload)
|
||||||
|
except Exception as exc:
|
||||||
|
last_exc = exc
|
||||||
|
if not _is_transient_error(exc):
|
||||||
|
raise
|
||||||
|
if attempt == attempts:
|
||||||
|
raise
|
||||||
|
sleep_s = _extract_retry_after_seconds(exc)
|
||||||
|
if sleep_s is None:
|
||||||
|
sleep_s = min(60.0, 2.0**attempt)
|
||||||
|
print(
|
||||||
|
f"{job_label} attempt {attempt}/{attempts} failed ({exc.__class__.__name__}); retrying in {sleep_s:.1f}s",
|
||||||
|
file=sys.stderr,
|
||||||
|
)
|
||||||
|
await asyncio.sleep(sleep_s)
|
||||||
|
raise last_exc or RuntimeError("unknown error")
|
||||||
|
|
||||||
|
|
||||||
|
async def _run_generate_batch(args: argparse.Namespace) -> int:
|
||||||
|
jobs = _read_jobs_jsonl(args.input)
|
||||||
|
out_dir = Path(args.out_dir)
|
||||||
|
|
||||||
|
base_fields = _fields_from_args(args)
|
||||||
|
base_payload = {
|
||||||
|
"model": args.model,
|
||||||
|
"n": args.n,
|
||||||
|
"size": args.size,
|
||||||
|
"quality": args.quality,
|
||||||
|
"background": args.background,
|
||||||
|
"output_format": args.output_format,
|
||||||
|
"output_compression": args.output_compression,
|
||||||
|
"moderation": args.moderation,
|
||||||
|
}
|
||||||
|
|
||||||
|
if args.dry_run:
|
||||||
|
for i, job in enumerate(jobs, start=1):
|
||||||
|
prompt = str(job["prompt"]).strip()
|
||||||
|
fields = _merge_non_null(base_fields, job.get("fields", {}))
|
||||||
|
# Allow flat job keys as well (use_case, scene, etc.)
|
||||||
|
fields = _merge_non_null(fields, {k: job.get(k) for k in base_fields.keys()})
|
||||||
|
augmented = _augment_prompt_fields(args.augment, prompt, fields)
|
||||||
|
|
||||||
|
job_payload = dict(base_payload)
|
||||||
|
job_payload["prompt"] = augmented
|
||||||
|
job_payload = _merge_non_null(job_payload, {k: job.get(k) for k in base_payload.keys()})
|
||||||
|
job_payload = {k: v for k, v in job_payload.items() if v is not None}
|
||||||
|
|
||||||
|
_validate_generate_payload(job_payload)
|
||||||
|
effective_output_format = _normalize_output_format(job_payload.get("output_format"))
|
||||||
|
_validate_transparency(job_payload.get("background"), effective_output_format)
|
||||||
|
job_payload["output_format"] = effective_output_format
|
||||||
|
|
||||||
|
n = int(job_payload.get("n", 1))
|
||||||
|
outputs = _job_output_paths(
|
||||||
|
out_dir=out_dir,
|
||||||
|
output_format=effective_output_format,
|
||||||
|
idx=i,
|
||||||
|
prompt=prompt,
|
||||||
|
n=n,
|
||||||
|
explicit_out=job.get("out"),
|
||||||
|
)
|
||||||
|
downscaled = None
|
||||||
|
if args.downscale_max_dim is not None:
|
||||||
|
downscaled = [
|
||||||
|
str(_derive_downscale_path(p, args.downscale_suffix)) for p in outputs
|
||||||
|
]
|
||||||
|
_print_request(
|
||||||
|
{
|
||||||
|
"endpoint": "/v1/images/generations",
|
||||||
|
"job": i,
|
||||||
|
"outputs": [str(p) for p in outputs],
|
||||||
|
"outputs_downscaled": downscaled,
|
||||||
|
**job_payload,
|
||||||
|
}
|
||||||
|
)
|
||||||
|
return 0
|
||||||
|
|
||||||
|
client = _create_async_client()
|
||||||
|
sem = asyncio.Semaphore(args.concurrency)
|
||||||
|
|
||||||
|
any_failed = False
|
||||||
|
|
||||||
|
async def run_job(i: int, job: Dict[str, Any]) -> Tuple[int, Optional[str]]:
|
||||||
|
nonlocal any_failed
|
||||||
|
prompt = str(job["prompt"]).strip()
|
||||||
|
job_label = f"[job {i}/{len(jobs)}]"
|
||||||
|
|
||||||
|
fields = _merge_non_null(base_fields, job.get("fields", {}))
|
||||||
|
fields = _merge_non_null(fields, {k: job.get(k) for k in base_fields.keys()})
|
||||||
|
augmented = _augment_prompt_fields(args.augment, prompt, fields)
|
||||||
|
|
||||||
|
payload = dict(base_payload)
|
||||||
|
payload["prompt"] = augmented
|
||||||
|
payload = _merge_non_null(payload, {k: job.get(k) for k in base_payload.keys()})
|
||||||
|
payload = {k: v for k, v in payload.items() if v is not None}
|
||||||
|
|
||||||
|
n = int(payload.get("n", 1))
|
||||||
|
_validate_generate_payload(payload)
|
||||||
|
effective_output_format = _normalize_output_format(payload.get("output_format"))
|
||||||
|
_validate_transparency(payload.get("background"), effective_output_format)
|
||||||
|
payload["output_format"] = effective_output_format
|
||||||
|
outputs = _job_output_paths(
|
||||||
|
out_dir=out_dir,
|
||||||
|
output_format=effective_output_format,
|
||||||
|
idx=i,
|
||||||
|
prompt=prompt,
|
||||||
|
n=n,
|
||||||
|
explicit_out=job.get("out"),
|
||||||
|
)
|
||||||
|
try:
|
||||||
|
async with sem:
|
||||||
|
print(f"{job_label} starting", file=sys.stderr)
|
||||||
|
started = time.time()
|
||||||
|
result = await _generate_one_with_retries(
|
||||||
|
client,
|
||||||
|
payload,
|
||||||
|
attempts=args.max_attempts,
|
||||||
|
job_label=job_label,
|
||||||
|
)
|
||||||
|
elapsed = time.time() - started
|
||||||
|
print(f"{job_label} completed in {elapsed:.1f}s", file=sys.stderr)
|
||||||
|
images = [item.b64_json for item in result.data]
|
||||||
|
_decode_write_and_downscale(
|
||||||
|
images,
|
||||||
|
outputs,
|
||||||
|
force=args.force,
|
||||||
|
downscale_max_dim=args.downscale_max_dim,
|
||||||
|
downscale_suffix=args.downscale_suffix,
|
||||||
|
output_format=effective_output_format,
|
||||||
|
)
|
||||||
|
return i, None
|
||||||
|
except Exception as exc:
|
||||||
|
any_failed = True
|
||||||
|
print(f"{job_label} failed: {exc}", file=sys.stderr)
|
||||||
|
if args.fail_fast:
|
||||||
|
raise
|
||||||
|
return i, str(exc)
|
||||||
|
|
||||||
|
tasks = [asyncio.create_task(run_job(i, job)) for i, job in enumerate(jobs, start=1)]
|
||||||
|
|
||||||
|
try:
|
||||||
|
await asyncio.gather(*tasks)
|
||||||
|
except Exception:
|
||||||
|
for t in tasks:
|
||||||
|
if not t.done():
|
||||||
|
t.cancel()
|
||||||
|
raise
|
||||||
|
|
||||||
|
return 1 if any_failed else 0
|
||||||
|
|
||||||
|
|
||||||
|
def _generate_batch(args: argparse.Namespace) -> None:
|
||||||
|
exit_code = asyncio.run(_run_generate_batch(args))
|
||||||
|
if exit_code:
|
||||||
|
raise SystemExit(exit_code)
|
||||||
|
|
||||||
|
|
||||||
|
def _generate(args: argparse.Namespace) -> None:
|
||||||
|
prompt = _read_prompt(args.prompt, args.prompt_file)
|
||||||
|
prompt = _augment_prompt(args, prompt)
|
||||||
|
|
||||||
|
payload = {
|
||||||
|
"model": args.model,
|
||||||
|
"prompt": prompt,
|
||||||
|
"n": args.n,
|
||||||
|
"size": args.size,
|
||||||
|
"quality": args.quality,
|
||||||
|
"background": args.background,
|
||||||
|
"output_format": args.output_format,
|
||||||
|
"output_compression": args.output_compression,
|
||||||
|
"moderation": args.moderation,
|
||||||
|
}
|
||||||
|
payload = {k: v for k, v in payload.items() if v is not None}
|
||||||
|
|
||||||
|
output_format = _normalize_output_format(args.output_format)
|
||||||
|
_validate_transparency(args.background, output_format)
|
||||||
|
payload["output_format"] = output_format
|
||||||
|
output_paths = _build_output_paths(args.out, output_format, args.n, args.out_dir)
|
||||||
|
downscaled = None
|
||||||
|
if args.downscale_max_dim is not None:
|
||||||
|
downscaled = [str(_derive_downscale_path(p, args.downscale_suffix)) for p in output_paths]
|
||||||
|
|
||||||
|
if args.dry_run:
|
||||||
|
_print_request(
|
||||||
|
{
|
||||||
|
"endpoint": "/v1/images/generations",
|
||||||
|
"outputs": [str(p) for p in output_paths],
|
||||||
|
"outputs_downscaled": downscaled,
|
||||||
|
**payload,
|
||||||
|
}
|
||||||
|
)
|
||||||
|
return
|
||||||
|
|
||||||
|
print(
|
||||||
|
"Calling Image API (generation). This can take up to a couple of minutes.",
|
||||||
|
file=sys.stderr,
|
||||||
|
)
|
||||||
|
started = time.time()
|
||||||
|
client = _create_client()
|
||||||
|
result = client.images.generate(**payload)
|
||||||
|
elapsed = time.time() - started
|
||||||
|
print(f"Generation completed in {elapsed:.1f}s.", file=sys.stderr)
|
||||||
|
|
||||||
|
images = [item.b64_json for item in result.data]
|
||||||
|
_decode_write_and_downscale(
|
||||||
|
images,
|
||||||
|
output_paths,
|
||||||
|
force=args.force,
|
||||||
|
downscale_max_dim=args.downscale_max_dim,
|
||||||
|
downscale_suffix=args.downscale_suffix,
|
||||||
|
output_format=output_format,
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
def _edit(args: argparse.Namespace) -> None:
|
||||||
|
prompt = _read_prompt(args.prompt, args.prompt_file)
|
||||||
|
prompt = _augment_prompt(args, prompt)
|
||||||
|
|
||||||
|
image_paths = _check_image_paths(args.image)
|
||||||
|
mask_path = Path(args.mask) if args.mask else None
|
||||||
|
if mask_path:
|
||||||
|
if not mask_path.exists():
|
||||||
|
_die(f"Mask file not found: {mask_path}")
|
||||||
|
if mask_path.suffix.lower() != ".png":
|
||||||
|
_warn(f"Mask should be a PNG with an alpha channel: {mask_path}")
|
||||||
|
if mask_path.stat().st_size > MAX_IMAGE_BYTES:
|
||||||
|
_warn(f"Mask exceeds 50MB limit: {mask_path}")
|
||||||
|
|
||||||
|
payload = {
|
||||||
|
"model": args.model,
|
||||||
|
"prompt": prompt,
|
||||||
|
"n": args.n,
|
||||||
|
"size": args.size,
|
||||||
|
"quality": args.quality,
|
||||||
|
"background": args.background,
|
||||||
|
"output_format": args.output_format,
|
||||||
|
"output_compression": args.output_compression,
|
||||||
|
"input_fidelity": args.input_fidelity,
|
||||||
|
"moderation": args.moderation,
|
||||||
|
}
|
||||||
|
payload = {k: v for k, v in payload.items() if v is not None}
|
||||||
|
|
||||||
|
output_format = _normalize_output_format(args.output_format)
|
||||||
|
_validate_transparency(args.background, output_format)
|
||||||
|
payload["output_format"] = output_format
|
||||||
|
_validate_input_fidelity(args.input_fidelity)
|
||||||
|
output_paths = _build_output_paths(args.out, output_format, args.n, args.out_dir)
|
||||||
|
downscaled = None
|
||||||
|
if args.downscale_max_dim is not None:
|
||||||
|
downscaled = [str(_derive_downscale_path(p, args.downscale_suffix)) for p in output_paths]
|
||||||
|
|
||||||
|
if args.dry_run:
|
||||||
|
payload_preview = dict(payload)
|
||||||
|
payload_preview["image"] = [str(p) for p in image_paths]
|
||||||
|
if mask_path:
|
||||||
|
payload_preview["mask"] = str(mask_path)
|
||||||
|
_print_request(
|
||||||
|
{
|
||||||
|
"endpoint": "/v1/images/edits",
|
||||||
|
"outputs": [str(p) for p in output_paths],
|
||||||
|
"outputs_downscaled": downscaled,
|
||||||
|
**payload_preview,
|
||||||
|
}
|
||||||
|
)
|
||||||
|
return
|
||||||
|
|
||||||
|
print(
|
||||||
|
f"Calling Image API (edit) with {len(image_paths)} image(s).",
|
||||||
|
file=sys.stderr,
|
||||||
|
)
|
||||||
|
started = time.time()
|
||||||
|
client = _create_client()
|
||||||
|
|
||||||
|
with _open_files(image_paths) as image_files, _open_mask(mask_path) as mask_file:
|
||||||
|
request = dict(payload)
|
||||||
|
request["image"] = image_files if len(image_files) > 1 else image_files[0]
|
||||||
|
if mask_file is not None:
|
||||||
|
request["mask"] = mask_file
|
||||||
|
result = client.images.edit(**request)
|
||||||
|
|
||||||
|
elapsed = time.time() - started
|
||||||
|
print(f"Edit completed in {elapsed:.1f}s.", file=sys.stderr)
|
||||||
|
images = [item.b64_json for item in result.data]
|
||||||
|
_decode_write_and_downscale(
|
||||||
|
images,
|
||||||
|
output_paths,
|
||||||
|
force=args.force,
|
||||||
|
downscale_max_dim=args.downscale_max_dim,
|
||||||
|
downscale_suffix=args.downscale_suffix,
|
||||||
|
output_format=output_format,
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
def _open_files(paths: List[Path]):
|
||||||
|
return _FileBundle(paths)
|
||||||
|
|
||||||
|
|
||||||
|
def _open_mask(mask_path: Optional[Path]):
|
||||||
|
if mask_path is None:
|
||||||
|
return _NullContext()
|
||||||
|
return _SingleFile(mask_path)
|
||||||
|
|
||||||
|
|
||||||
|
class _NullContext:
|
||||||
|
def __enter__(self):
|
||||||
|
return None
|
||||||
|
|
||||||
|
def __exit__(self, exc_type, exc, tb):
|
||||||
|
return False
|
||||||
|
|
||||||
|
|
||||||
|
class _SingleFile:
|
||||||
|
def __init__(self, path: Path):
|
||||||
|
self._path = path
|
||||||
|
self._handle = None
|
||||||
|
|
||||||
|
def __enter__(self):
|
||||||
|
self._handle = self._path.open("rb")
|
||||||
|
return self._handle
|
||||||
|
|
||||||
|
def __exit__(self, exc_type, exc, tb):
|
||||||
|
if self._handle:
|
||||||
|
try:
|
||||||
|
self._handle.close()
|
||||||
|
except Exception:
|
||||||
|
pass
|
||||||
|
return False
|
||||||
|
|
||||||
|
|
||||||
|
class _FileBundle:
|
||||||
|
def __init__(self, paths: List[Path]):
|
||||||
|
self._paths = paths
|
||||||
|
self._handles: List[object] = []
|
||||||
|
|
||||||
|
def __enter__(self):
|
||||||
|
self._handles = [p.open("rb") for p in self._paths]
|
||||||
|
return self._handles
|
||||||
|
|
||||||
|
def __exit__(self, exc_type, exc, tb):
|
||||||
|
for handle in self._handles:
|
||||||
|
try:
|
||||||
|
handle.close()
|
||||||
|
except Exception:
|
||||||
|
pass
|
||||||
|
return False
|
||||||
|
|
||||||
|
|
||||||
|
def _add_shared_args(parser: argparse.ArgumentParser) -> None:
|
||||||
|
parser.add_argument("--model", default=DEFAULT_MODEL)
|
||||||
|
parser.add_argument("--prompt")
|
||||||
|
parser.add_argument("--prompt-file")
|
||||||
|
parser.add_argument("--n", type=int, default=1)
|
||||||
|
parser.add_argument("--size", default=DEFAULT_SIZE)
|
||||||
|
parser.add_argument("--quality", default=DEFAULT_QUALITY)
|
||||||
|
parser.add_argument("--background")
|
||||||
|
parser.add_argument("--output-format")
|
||||||
|
parser.add_argument("--output-compression", type=int)
|
||||||
|
parser.add_argument("--moderation")
|
||||||
|
parser.add_argument("--out", default=DEFAULT_OUTPUT_PATH)
|
||||||
|
parser.add_argument("--out-dir")
|
||||||
|
parser.add_argument("--force", action="store_true")
|
||||||
|
parser.add_argument("--dry-run", action="store_true")
|
||||||
|
parser.add_argument("--augment", dest="augment", action="store_true")
|
||||||
|
parser.add_argument("--no-augment", dest="augment", action="store_false")
|
||||||
|
parser.set_defaults(augment=True)
|
||||||
|
|
||||||
|
# Prompt augmentation hints
|
||||||
|
parser.add_argument("--use-case")
|
||||||
|
parser.add_argument("--scene")
|
||||||
|
parser.add_argument("--subject")
|
||||||
|
parser.add_argument("--style")
|
||||||
|
parser.add_argument("--composition")
|
||||||
|
parser.add_argument("--lighting")
|
||||||
|
parser.add_argument("--palette")
|
||||||
|
parser.add_argument("--materials")
|
||||||
|
parser.add_argument("--text")
|
||||||
|
parser.add_argument("--constraints")
|
||||||
|
parser.add_argument("--negative")
|
||||||
|
|
||||||
|
# Post-processing (optional): generate an additional downscaled copy for fast web loading.
|
||||||
|
parser.add_argument("--downscale-max-dim", type=int)
|
||||||
|
parser.add_argument("--downscale-suffix", default=DEFAULT_DOWNSCALE_SUFFIX)
|
||||||
|
|
||||||
|
|
||||||
|
def main() -> int:
|
||||||
|
parser = argparse.ArgumentParser(
|
||||||
|
description="Fallback CLI for explicit image generation or editing via GPT Image models"
|
||||||
|
)
|
||||||
|
subparsers = parser.add_subparsers(dest="command", required=True)
|
||||||
|
|
||||||
|
gen_parser = subparsers.add_parser("generate", help="Create a new image")
|
||||||
|
_add_shared_args(gen_parser)
|
||||||
|
gen_parser.set_defaults(func=_generate)
|
||||||
|
|
||||||
|
batch_parser = subparsers.add_parser(
|
||||||
|
"generate-batch",
|
||||||
|
help="Generate multiple prompts concurrently (JSONL input)",
|
||||||
|
)
|
||||||
|
_add_shared_args(batch_parser)
|
||||||
|
batch_parser.add_argument("--input", required=True, help="Path to JSONL file (one job per line)")
|
||||||
|
batch_parser.add_argument("--concurrency", type=int, default=DEFAULT_CONCURRENCY)
|
||||||
|
batch_parser.add_argument("--max-attempts", type=int, default=3)
|
||||||
|
batch_parser.add_argument("--fail-fast", action="store_true")
|
||||||
|
batch_parser.set_defaults(func=_generate_batch)
|
||||||
|
|
||||||
|
edit_parser = subparsers.add_parser("edit", help="Edit an existing image")
|
||||||
|
_add_shared_args(edit_parser)
|
||||||
|
edit_parser.add_argument("--image", action="append", required=True)
|
||||||
|
edit_parser.add_argument("--mask")
|
||||||
|
edit_parser.add_argument("--input-fidelity")
|
||||||
|
edit_parser.set_defaults(func=_edit)
|
||||||
|
|
||||||
|
args = parser.parse_args()
|
||||||
|
if args.n < 1 or args.n > 10:
|
||||||
|
_die("--n must be between 1 and 10")
|
||||||
|
if getattr(args, "concurrency", 1) < 1 or getattr(args, "concurrency", 1) > 25:
|
||||||
|
_die("--concurrency must be between 1 and 25")
|
||||||
|
if getattr(args, "max_attempts", 3) < 1 or getattr(args, "max_attempts", 3) > 10:
|
||||||
|
_die("--max-attempts must be between 1 and 10")
|
||||||
|
if args.output_compression is not None and not (0 <= args.output_compression <= 100):
|
||||||
|
_die("--output-compression must be between 0 and 100")
|
||||||
|
if args.command == "generate-batch" and not args.out_dir:
|
||||||
|
_die("generate-batch requires --out-dir")
|
||||||
|
if getattr(args, "downscale_max_dim", None) is not None and args.downscale_max_dim < 1:
|
||||||
|
_die("--downscale-max-dim must be >= 1")
|
||||||
|
|
||||||
|
_validate_model(args.model)
|
||||||
|
_validate_size(args.size, args.model)
|
||||||
|
_validate_quality(args.quality)
|
||||||
|
_validate_background(args.background)
|
||||||
|
_validate_model_specific_options(
|
||||||
|
model=args.model,
|
||||||
|
background=args.background,
|
||||||
|
input_fidelity=getattr(args, "input_fidelity", None),
|
||||||
|
)
|
||||||
|
_ensure_api_key(args.dry_run)
|
||||||
|
|
||||||
|
args.func(args)
|
||||||
|
return 0
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
raise SystemExit(main())
|
||||||
440
skills/.system/imagegen/scripts/remove_chroma_key.py
Normal file
440
skills/.system/imagegen/scripts/remove_chroma_key.py
Normal file
@ -0,0 +1,440 @@
|
|||||||
|
#!/usr/bin/env python3
|
||||||
|
"""Remove a solid chroma-key background from an image.
|
||||||
|
|
||||||
|
This helper supports the imagegen skill's built-in-first transparent workflow:
|
||||||
|
generate an image on a flat key color, then convert that key color to alpha.
|
||||||
|
"""
|
||||||
|
|
||||||
|
from __future__ import annotations
|
||||||
|
|
||||||
|
import argparse
|
||||||
|
from io import BytesIO
|
||||||
|
from pathlib import Path
|
||||||
|
import re
|
||||||
|
from statistics import median
|
||||||
|
import sys
|
||||||
|
from typing import Tuple
|
||||||
|
|
||||||
|
|
||||||
|
Color = Tuple[int, int, int]
|
||||||
|
KEY_DOMINANCE_THRESHOLD = 16.0
|
||||||
|
ALPHA_NOISE_FLOOR = 8
|
||||||
|
|
||||||
|
|
||||||
|
def _die(message: str, code: int = 1) -> None:
|
||||||
|
print(f"Error: {message}", file=sys.stderr)
|
||||||
|
raise SystemExit(code)
|
||||||
|
|
||||||
|
|
||||||
|
def _dependency_hint(package: str) -> str:
|
||||||
|
return (
|
||||||
|
"Activate the repo-selected environment first, then install it with "
|
||||||
|
f"`uv pip install {package}`. If this repo uses a local virtualenv, start with "
|
||||||
|
"`source .venv/bin/activate`; otherwise use this repo's configured shared fallback "
|
||||||
|
"environment."
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
def _load_pillow():
|
||||||
|
try:
|
||||||
|
from PIL import Image, ImageFilter
|
||||||
|
except ImportError:
|
||||||
|
_die(f"Pillow is required for chroma-key removal. {_dependency_hint('pillow')}")
|
||||||
|
return Image, ImageFilter
|
||||||
|
|
||||||
|
|
||||||
|
def _parse_key_color(raw: str) -> Color:
|
||||||
|
value = raw.strip()
|
||||||
|
match = re.fullmatch(r"#?([0-9a-fA-F]{6})", value)
|
||||||
|
if not match:
|
||||||
|
_die("key color must be a hex RGB value like #00ff00.")
|
||||||
|
hex_value = match.group(1)
|
||||||
|
return (
|
||||||
|
int(hex_value[0:2], 16),
|
||||||
|
int(hex_value[2:4], 16),
|
||||||
|
int(hex_value[4:6], 16),
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
def _validate_args(args: argparse.Namespace) -> None:
|
||||||
|
if args.tolerance < 0 or args.tolerance > 255:
|
||||||
|
_die("--tolerance must be between 0 and 255.")
|
||||||
|
if args.transparent_threshold < 0 or args.transparent_threshold > 255:
|
||||||
|
_die("--transparent-threshold must be between 0 and 255.")
|
||||||
|
if args.opaque_threshold < 0 or args.opaque_threshold > 255:
|
||||||
|
_die("--opaque-threshold must be between 0 and 255.")
|
||||||
|
if args.soft_matte and args.transparent_threshold >= args.opaque_threshold:
|
||||||
|
_die("--transparent-threshold must be lower than --opaque-threshold.")
|
||||||
|
if args.edge_feather < 0 or args.edge_feather > 64:
|
||||||
|
_die("--edge-feather must be between 0 and 64.")
|
||||||
|
if args.edge_contract < 0 or args.edge_contract > 16:
|
||||||
|
_die("--edge-contract must be between 0 and 16.")
|
||||||
|
|
||||||
|
src = Path(args.input)
|
||||||
|
if not src.exists():
|
||||||
|
_die(f"Input image not found: {src}")
|
||||||
|
|
||||||
|
out = Path(args.out)
|
||||||
|
if out.exists() and not args.force:
|
||||||
|
_die(f"Output already exists: {out} (use --force to overwrite)")
|
||||||
|
|
||||||
|
if out.suffix.lower() not in {".png", ".webp"}:
|
||||||
|
_die("--out must end in .png or .webp so the alpha channel is preserved.")
|
||||||
|
|
||||||
|
|
||||||
|
def _channel_distance(a: Color, b: Color) -> int:
|
||||||
|
return max(abs(a[0] - b[0]), abs(a[1] - b[1]), abs(a[2] - b[2]))
|
||||||
|
|
||||||
|
|
||||||
|
def _clamp_channel(value: float) -> int:
|
||||||
|
return max(0, min(255, int(round(value))))
|
||||||
|
|
||||||
|
|
||||||
|
def _smoothstep(value: float) -> float:
|
||||||
|
value = max(0.0, min(1.0, value))
|
||||||
|
return value * value * (3.0 - 2.0 * value)
|
||||||
|
|
||||||
|
|
||||||
|
def _soft_alpha(distance: int, transparent_threshold: float, opaque_threshold: float) -> int:
|
||||||
|
if distance <= transparent_threshold:
|
||||||
|
return 0
|
||||||
|
if distance >= opaque_threshold:
|
||||||
|
return 255
|
||||||
|
ratio = (float(distance) - transparent_threshold) / (
|
||||||
|
opaque_threshold - transparent_threshold
|
||||||
|
)
|
||||||
|
return _clamp_channel(255.0 * _smoothstep(ratio))
|
||||||
|
|
||||||
|
|
||||||
|
def _dominance_alpha(rgb: Color, key: Color) -> int:
|
||||||
|
spill_channels = _spill_channels(key)
|
||||||
|
if not spill_channels:
|
||||||
|
return 255
|
||||||
|
|
||||||
|
channels = [float(value) for value in rgb]
|
||||||
|
non_spill = [idx for idx in range(3) if idx not in spill_channels]
|
||||||
|
key_strength = (
|
||||||
|
min(channels[idx] for idx in spill_channels)
|
||||||
|
if len(spill_channels) > 1
|
||||||
|
else channels[spill_channels[0]]
|
||||||
|
)
|
||||||
|
non_key_strength = max((channels[idx] for idx in non_spill), default=0.0)
|
||||||
|
dominance = key_strength - non_key_strength
|
||||||
|
if dominance <= 0:
|
||||||
|
return 255
|
||||||
|
|
||||||
|
denominator = max(1.0, float(max(key)) - non_key_strength)
|
||||||
|
alpha = 1.0 - min(1.0, dominance / denominator)
|
||||||
|
return _clamp_channel(alpha * 255.0)
|
||||||
|
|
||||||
|
|
||||||
|
def _spill_channels(key: Color) -> list[int]:
|
||||||
|
key_max = max(key)
|
||||||
|
if key_max < 128:
|
||||||
|
return []
|
||||||
|
return [idx for idx, value in enumerate(key) if value >= key_max - 16 and value >= 128]
|
||||||
|
|
||||||
|
|
||||||
|
def _key_channel_dominance(rgb: Color, key: Color) -> float:
|
||||||
|
spill_channels = _spill_channels(key)
|
||||||
|
if not spill_channels:
|
||||||
|
return 0.0
|
||||||
|
|
||||||
|
channels = [float(value) for value in rgb]
|
||||||
|
non_spill = [idx for idx in range(3) if idx not in spill_channels]
|
||||||
|
key_strength = (
|
||||||
|
min(channels[idx] for idx in spill_channels)
|
||||||
|
if len(spill_channels) > 1
|
||||||
|
else channels[spill_channels[0]]
|
||||||
|
)
|
||||||
|
non_key_strength = max((channels[idx] for idx in non_spill), default=0.0)
|
||||||
|
return key_strength - non_key_strength
|
||||||
|
|
||||||
|
|
||||||
|
def _looks_key_colored(rgb: Color, key: Color, distance: int) -> bool:
|
||||||
|
if distance <= 32:
|
||||||
|
return True
|
||||||
|
|
||||||
|
spill_channels = _spill_channels(key)
|
||||||
|
if not spill_channels:
|
||||||
|
return True
|
||||||
|
|
||||||
|
return _key_channel_dominance(rgb, key) >= KEY_DOMINANCE_THRESHOLD
|
||||||
|
|
||||||
|
|
||||||
|
def _cleanup_spill(rgb: Color, key: Color, alpha: int = 255) -> Color:
|
||||||
|
if alpha >= 252:
|
||||||
|
return rgb
|
||||||
|
|
||||||
|
spill_channels = _spill_channels(key)
|
||||||
|
if not spill_channels:
|
||||||
|
return rgb
|
||||||
|
|
||||||
|
channels = [float(value) for value in rgb]
|
||||||
|
non_spill = [idx for idx in range(3) if idx not in spill_channels]
|
||||||
|
if non_spill:
|
||||||
|
anchor = max(channels[idx] for idx in non_spill)
|
||||||
|
cap = max(0.0, anchor - 1.0)
|
||||||
|
for idx in spill_channels:
|
||||||
|
if channels[idx] > cap:
|
||||||
|
channels[idx] = cap
|
||||||
|
|
||||||
|
return (
|
||||||
|
_clamp_channel(channels[0]),
|
||||||
|
_clamp_channel(channels[1]),
|
||||||
|
_clamp_channel(channels[2]),
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
def _apply_alpha_to_image(
|
||||||
|
image,
|
||||||
|
*,
|
||||||
|
key: Color,
|
||||||
|
tolerance: int,
|
||||||
|
spill_cleanup: bool,
|
||||||
|
soft_matte: bool,
|
||||||
|
transparent_threshold: float,
|
||||||
|
opaque_threshold: float,
|
||||||
|
) -> int:
|
||||||
|
pixels = image.load()
|
||||||
|
width, height = image.size
|
||||||
|
transparent = 0
|
||||||
|
|
||||||
|
for y in range(height):
|
||||||
|
for x in range(width):
|
||||||
|
red, green, blue, alpha = pixels[x, y]
|
||||||
|
rgb = (red, green, blue)
|
||||||
|
distance = _channel_distance(rgb, key)
|
||||||
|
key_like = _looks_key_colored(rgb, key, distance)
|
||||||
|
output_alpha = (
|
||||||
|
min(
|
||||||
|
_soft_alpha(distance, transparent_threshold, opaque_threshold),
|
||||||
|
_dominance_alpha(rgb, key),
|
||||||
|
)
|
||||||
|
if soft_matte and key_like
|
||||||
|
else (0 if distance <= tolerance else 255)
|
||||||
|
)
|
||||||
|
output_alpha = int(round(output_alpha * (alpha / 255.0)))
|
||||||
|
if 0 < output_alpha <= ALPHA_NOISE_FLOOR:
|
||||||
|
output_alpha = 0
|
||||||
|
|
||||||
|
if output_alpha == 0:
|
||||||
|
pixels[x, y] = (0, 0, 0, 0)
|
||||||
|
transparent += 1
|
||||||
|
continue
|
||||||
|
|
||||||
|
if spill_cleanup and key_like:
|
||||||
|
red, green, blue = _cleanup_spill(rgb, key, output_alpha)
|
||||||
|
pixels[x, y] = (red, green, blue, output_alpha)
|
||||||
|
|
||||||
|
return transparent
|
||||||
|
|
||||||
|
|
||||||
|
def _contract_alpha(image, pixels: int):
|
||||||
|
if pixels == 0:
|
||||||
|
return image
|
||||||
|
|
||||||
|
_, ImageFilter = _load_pillow()
|
||||||
|
alpha = image.getchannel("A")
|
||||||
|
for _ in range(pixels):
|
||||||
|
alpha = alpha.filter(ImageFilter.MinFilter(3))
|
||||||
|
image.putalpha(alpha)
|
||||||
|
return image
|
||||||
|
|
||||||
|
|
||||||
|
def _apply_edge_feather(image, radius: float):
|
||||||
|
if radius == 0:
|
||||||
|
return image
|
||||||
|
|
||||||
|
_, ImageFilter = _load_pillow()
|
||||||
|
alpha = image.getchannel("A")
|
||||||
|
alpha = alpha.filter(ImageFilter.GaussianBlur(radius=radius))
|
||||||
|
image.putalpha(alpha)
|
||||||
|
return image
|
||||||
|
|
||||||
|
|
||||||
|
def _encode_image(image, output_format: str) -> bytes:
|
||||||
|
out = BytesIO()
|
||||||
|
image.save(out, format=output_format.upper())
|
||||||
|
return out.getvalue()
|
||||||
|
|
||||||
|
|
||||||
|
def _alpha_counts(image) -> tuple[int, int, int]:
|
||||||
|
pixels = image.load()
|
||||||
|
width, height = image.size
|
||||||
|
total = 0
|
||||||
|
transparent = 0
|
||||||
|
partial = 0
|
||||||
|
|
||||||
|
for y in range(height):
|
||||||
|
for x in range(width):
|
||||||
|
alpha = pixels[x, y][3]
|
||||||
|
total += 1
|
||||||
|
if alpha == 0:
|
||||||
|
transparent += 1
|
||||||
|
elif alpha < 255:
|
||||||
|
partial += 1
|
||||||
|
|
||||||
|
return total, transparent, partial
|
||||||
|
|
||||||
|
|
||||||
|
def _sample_border_key(image, mode: str) -> Color:
|
||||||
|
width, height = image.size
|
||||||
|
pixels = image.load()
|
||||||
|
samples: list[Color] = []
|
||||||
|
|
||||||
|
if mode == "corners":
|
||||||
|
patch = max(1, min(width, height, 12))
|
||||||
|
boxes = [
|
||||||
|
(0, 0, patch, patch),
|
||||||
|
(width - patch, 0, width, patch),
|
||||||
|
(0, height - patch, patch, height),
|
||||||
|
(width - patch, height - patch, width, height),
|
||||||
|
]
|
||||||
|
for left, top, right, bottom in boxes:
|
||||||
|
for y in range(top, bottom):
|
||||||
|
for x in range(left, right):
|
||||||
|
red, green, blue = pixels[x, y][:3]
|
||||||
|
samples.append((red, green, blue))
|
||||||
|
else:
|
||||||
|
band = max(1, min(width, height, 6))
|
||||||
|
step = max(1, min(width, height) // 256)
|
||||||
|
for x in range(0, width, step):
|
||||||
|
for y in range(band):
|
||||||
|
red, green, blue = pixels[x, y][:3]
|
||||||
|
samples.append((red, green, blue))
|
||||||
|
red, green, blue = pixels[x, height - 1 - y][:3]
|
||||||
|
samples.append((red, green, blue))
|
||||||
|
for y in range(0, height, step):
|
||||||
|
for x in range(band):
|
||||||
|
red, green, blue = pixels[x, y][:3]
|
||||||
|
samples.append((red, green, blue))
|
||||||
|
red, green, blue = pixels[width - 1 - x, y][:3]
|
||||||
|
samples.append((red, green, blue))
|
||||||
|
|
||||||
|
if not samples:
|
||||||
|
_die("Could not sample background key color from image border.")
|
||||||
|
|
||||||
|
return (
|
||||||
|
int(round(median(sample[0] for sample in samples))),
|
||||||
|
int(round(median(sample[1] for sample in samples))),
|
||||||
|
int(round(median(sample[2] for sample in samples))),
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
def _remove_chroma_key(args: argparse.Namespace) -> None:
|
||||||
|
Image, _ = _load_pillow()
|
||||||
|
src = Path(args.input)
|
||||||
|
out = Path(args.out)
|
||||||
|
|
||||||
|
with Image.open(src) as image:
|
||||||
|
rgba = image.convert("RGBA")
|
||||||
|
key = (
|
||||||
|
_sample_border_key(rgba, args.auto_key)
|
||||||
|
if args.auto_key != "none"
|
||||||
|
else _parse_key_color(args.key_color)
|
||||||
|
)
|
||||||
|
|
||||||
|
transparent = _apply_alpha_to_image(
|
||||||
|
rgba,
|
||||||
|
key=key,
|
||||||
|
tolerance=args.tolerance,
|
||||||
|
spill_cleanup=args.spill_cleanup,
|
||||||
|
soft_matte=args.soft_matte,
|
||||||
|
transparent_threshold=args.transparent_threshold,
|
||||||
|
opaque_threshold=args.opaque_threshold,
|
||||||
|
)
|
||||||
|
rgba = _contract_alpha(rgba, args.edge_contract)
|
||||||
|
rgba = _apply_edge_feather(rgba, args.edge_feather)
|
||||||
|
|
||||||
|
total, transparent_after, partial_after = _alpha_counts(rgba)
|
||||||
|
|
||||||
|
out.parent.mkdir(parents=True, exist_ok=True)
|
||||||
|
output_format = "PNG" if out.suffix.lower() == ".png" else "WEBP"
|
||||||
|
out.write_bytes(_encode_image(rgba, output_format))
|
||||||
|
|
||||||
|
print(f"Wrote {out}")
|
||||||
|
print(f"Key color: #{key[0]:02x}{key[1]:02x}{key[2]:02x}")
|
||||||
|
print(f"Transparent pixels: {transparent_after}/{total}")
|
||||||
|
print(f"Partially transparent pixels: {partial_after}/{total}")
|
||||||
|
if transparent == 0:
|
||||||
|
print("Warning: no pixels matched the key color before feathering.", file=sys.stderr)
|
||||||
|
|
||||||
|
|
||||||
|
def _build_parser() -> argparse.ArgumentParser:
|
||||||
|
parser = argparse.ArgumentParser(
|
||||||
|
description="Remove a solid chroma-key background and write an image with alpha."
|
||||||
|
)
|
||||||
|
parser.add_argument("--input", required=True, help="Input image path.")
|
||||||
|
parser.add_argument("--out", required=True, help="Output .png or .webp path.")
|
||||||
|
parser.add_argument(
|
||||||
|
"--key-color",
|
||||||
|
default="#00ff00",
|
||||||
|
help="Hex RGB key color to remove, for example #00ff00.",
|
||||||
|
)
|
||||||
|
parser.add_argument(
|
||||||
|
"--tolerance",
|
||||||
|
type=int,
|
||||||
|
default=12,
|
||||||
|
help="Hard-key per-channel tolerance for matching the key color, 0-255.",
|
||||||
|
)
|
||||||
|
parser.add_argument(
|
||||||
|
"--auto-key",
|
||||||
|
choices=["none", "corners", "border"],
|
||||||
|
default="none",
|
||||||
|
help="Sample the key color from image corners or border instead of --key-color.",
|
||||||
|
)
|
||||||
|
parser.add_argument(
|
||||||
|
"--soft-matte",
|
||||||
|
action="store_true",
|
||||||
|
help="Use a smooth alpha ramp between transparent and opaque thresholds.",
|
||||||
|
)
|
||||||
|
parser.add_argument(
|
||||||
|
"--transparent-threshold",
|
||||||
|
type=float,
|
||||||
|
default=12.0,
|
||||||
|
help="Soft-matte distance at or below which pixels become fully transparent.",
|
||||||
|
)
|
||||||
|
parser.add_argument(
|
||||||
|
"--opaque-threshold",
|
||||||
|
type=float,
|
||||||
|
default=96.0,
|
||||||
|
help="Soft-matte distance at or above which pixels become fully opaque.",
|
||||||
|
)
|
||||||
|
parser.add_argument(
|
||||||
|
"--edge-feather",
|
||||||
|
type=float,
|
||||||
|
default=0.0,
|
||||||
|
help="Optional alpha blur radius for softened edges, 0-64.",
|
||||||
|
)
|
||||||
|
parser.add_argument(
|
||||||
|
"--edge-contract",
|
||||||
|
type=int,
|
||||||
|
default=0,
|
||||||
|
help="Shrink the visible alpha matte by this many pixels before feathering.",
|
||||||
|
)
|
||||||
|
parser.add_argument(
|
||||||
|
"--spill-cleanup",
|
||||||
|
dest="spill_cleanup",
|
||||||
|
action="store_true",
|
||||||
|
help="Reduce obvious key-color spill on opaque pixels.",
|
||||||
|
)
|
||||||
|
parser.add_argument(
|
||||||
|
"--despill",
|
||||||
|
dest="spill_cleanup",
|
||||||
|
action="store_true",
|
||||||
|
help="Alias for --spill-cleanup; decontaminate key-color edge spill.",
|
||||||
|
)
|
||||||
|
parser.add_argument("--force", action="store_true", help="Overwrite an existing output file.")
|
||||||
|
return parser
|
||||||
|
|
||||||
|
|
||||||
|
def main() -> None:
|
||||||
|
parser = _build_parser()
|
||||||
|
args = parser.parse_args()
|
||||||
|
_validate_args(args)
|
||||||
|
_remove_chroma_key(args)
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
main()
|
||||||
201
skills/.system/openai-docs/LICENSE.txt
Normal file
201
skills/.system/openai-docs/LICENSE.txt
Normal file
@ -0,0 +1,201 @@
|
|||||||
|
Apache License
|
||||||
|
Version 2.0, January 2004
|
||||||
|
http://www.apache.org/licenses/
|
||||||
|
|
||||||
|
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
|
||||||
|
|
||||||
|
1. Definitions.
|
||||||
|
|
||||||
|
"License" shall mean the terms and conditions for use, reproduction,
|
||||||
|
and distribution as defined by Sections 1 through 9 of this document.
|
||||||
|
|
||||||
|
"Licensor" shall mean the copyright owner or entity authorized by
|
||||||
|
the copyright owner that is granting the License.
|
||||||
|
|
||||||
|
"Legal Entity" shall mean the union of the acting entity and all
|
||||||
|
other entities that control, are controlled by, or are under common
|
||||||
|
control with that entity. For the purposes of this definition,
|
||||||
|
"control" means (i) the power, direct or indirect, to cause the
|
||||||
|
direction or management of such entity, whether by contract or
|
||||||
|
otherwise, or (ii) ownership of fifty percent (50%) or more of the
|
||||||
|
outstanding shares, or (iii) beneficial ownership of such entity.
|
||||||
|
|
||||||
|
"You" (or "Your") shall mean an individual or Legal Entity
|
||||||
|
exercising permissions granted by this License.
|
||||||
|
|
||||||
|
"Source" form shall mean the preferred form for making modifications,
|
||||||
|
including but not limited to software source code, documentation
|
||||||
|
source, and configuration files.
|
||||||
|
|
||||||
|
"Object" form shall mean any form resulting from mechanical
|
||||||
|
transformation or translation of a Source form, including but
|
||||||
|
not limited to compiled object code, generated documentation,
|
||||||
|
and conversions to other media types.
|
||||||
|
|
||||||
|
"Work" shall mean the work of authorship, whether in Source or
|
||||||
|
Object form, made available under the License, as indicated by a
|
||||||
|
copyright notice that is included in or attached to the work
|
||||||
|
(an example is provided in the Appendix below).
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||||||
|
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|
"Derivative Works" shall mean any work, whether in Source or Object
|
||||||
|
form, that is based on (or derived from) the Work and for which the
|
||||||
|
editorial revisions, annotations, elaborations, or other modifications
|
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|
represent, as a whole, an original work of authorship. For the purposes
|
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of this License, Derivative Works shall not include works that remain
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|
||||||
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||||||
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||||||
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"Contribution" shall mean any work of authorship, including
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|
||||||
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|
||||||
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excluding communication that is conspicuously marked or otherwise
|
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||||||
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"Contributor" shall mean Licensor and any individual or Legal Entity
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||||||
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|
||||||
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2. Grant of Copyright License. Subject to the terms and conditions of
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||||||
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|
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3. Grant of Patent License. Subject to the terms and conditions of
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with the Work to which such Contribution(s) was submitted. If You
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or a Contribution incorporated within the Work constitutes direct
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granted to You under this License for that Work shall terminate
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||||||
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as of the date such litigation is filed.
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||||||
|
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|
4. Redistribution. You may reproduce and distribute copies of the
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Work or Derivative Works thereof in any medium, with or without
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modifications, and in Source or Object form, provided that You
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meet the following conditions:
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(a) You must give any other recipients of the Work or
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Derivative Works a copy of this License; and
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(b) You must cause any modified files to carry prominent notices
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||||||
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stating that You changed the files; and
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|
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(c) You must retain, in the Source form of any Derivative Works
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(d) If the Work includes a "NOTICE" text file as part of its
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distribution, then any Derivative Works that You distribute must
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5. Submission of Contributions. Unless You explicitly state otherwise,
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|
of your accepting any such warranty or additional liability.
|
||||||
|
|
||||||
|
END OF TERMS AND CONDITIONS
|
||||||
|
|
||||||
|
APPENDIX: How to apply the Apache License to your work.
|
||||||
|
|
||||||
|
To apply the Apache License to your work, attach the following
|
||||||
|
boilerplate notice, with the fields enclosed by brackets "[]"
|
||||||
|
replaced with your own identifying information. (Don\'t include
|
||||||
|
the brackets!) The text should be enclosed in the appropriate
|
||||||
|
comment syntax for the file format. We also recommend that a
|
||||||
|
file or class name and description of purpose be included on the
|
||||||
|
same "printed page" as the copyright notice for easier
|
||||||
|
identification within third-party archives.
|
||||||
|
|
||||||
|
Copyright [yyyy] [name of copyright owner]
|
||||||
|
|
||||||
|
Licensed under the Apache License, Version 2.0 (the "License");
|
||||||
|
you may not use this file except in compliance with the License.
|
||||||
|
You may obtain a copy of the License at
|
||||||
|
|
||||||
|
http://www.apache.org/licenses/LICENSE-2.0
|
||||||
|
|
||||||
|
Unless required by applicable law or agreed to in writing, software
|
||||||
|
distributed under the License is distributed on an "AS IS" BASIS,
|
||||||
|
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||||
|
See the License for the specific language governing permissions and
|
||||||
|
limitations under the License.
|
||||||
183
skills/.system/openai-docs/SKILL.md
Normal file
183
skills/.system/openai-docs/SKILL.md
Normal file
@ -0,0 +1,183 @@
|
|||||||
|
---
|
||||||
|
name: "openai-docs"
|
||||||
|
description: "Use when the user asks how to build with OpenAI products or APIs, asks about Codex itself or choosing Codex surfaces, needs up-to-date official documentation with citations, help choosing the latest model for a use case, latest/current/default-model prompting guidance, or model upgrade and prompt-upgrade guidance; use OpenAI docs MCP tools for non-Codex docs questions, use the Codex manual helper first for broad Codex self-knowledge, and restrict fallback browsing to official OpenAI domains."
|
||||||
|
---
|
||||||
|
|
||||||
|
|
||||||
|
# OpenAI Docs
|
||||||
|
|
||||||
|
Provide authoritative, current guidance from OpenAI developer docs using the developers.openai.com MCP server. "Docs MCP" means `mcp__openaiDeveloperDocs__search_openai_docs` and `mcp__openaiDeveloperDocs__fetch_openai_doc`; for API reference, schema, parameter, or required-field questions, also use `mcp__openaiDeveloperDocs__get_openapi_spec` when available. Official-domain web search is fallback after those tools are unavailable or unhelpful. Broad Codex questions use the manual helper before Docs MCP. This skill also owns model selection, API model migration, and prompt-upgrade guidance.
|
||||||
|
|
||||||
|
## API Key Setup
|
||||||
|
|
||||||
|
For requests to build, run, configure, debug, or implement an API-backed app, script, CLI, generator, or tool, use `openai-platform-api-key` first when available. After that credential gate is resolved, return here for current docs as needed.
|
||||||
|
|
||||||
|
Use this skill directly for docs-only questions, citations, model/API guidance, conceptual explanations, and examples that do not require building or running an API-backed artifact.
|
||||||
|
|
||||||
|
For latest/current/default/unspecified model migration or prompting-guidance requests, complete the read-only latest-model resolver and guide fetch before the API-key credential gate. The credential gate still blocks edits, tests, and API-backed implementation until resolved; it does not block read-only retrieval of current model, migration, or prompting guidance.
|
||||||
|
|
||||||
|
## First action for latest-model changes
|
||||||
|
|
||||||
|
Before reading memory, inspecting the repo, fetching docs, or checking API credentials, classify the request:
|
||||||
|
|
||||||
|
- **Latest/current prompting guidance, or change requested + latest/current/newest/recommended/default/flagship/unspecified target:** immediately run the resolver with the platform-specific command below and inspect its JSON output. This includes asking how to prompt the latest model, changing prompts, a model picker, model references, an SDK integration, replacing an older named model with "the current model", or asking "which model should I migrate/upgrade to?". Do not directly fetch `latest-model.md` for this branch.
|
||||||
|
- **Pure model-selection question only, with no prompting guidance or requested change:** directly fetch `https://developers.openai.com/api/docs/guides/latest-model.md`; do not run the resolver.
|
||||||
|
- **Change requested + explicit target model:** preserve that target; do not run the latest-model resolver. For an explicit GPT-5.6 Sol or GPT-5.6-family migration, fetch the live GPT-5.6 model-guidance page and read `references/upgrading-to-gpt-5p6-sol.md` for skill-specific migration judgment.
|
||||||
|
- **Prompting or migration guidance for an explicitly named GPT-5-family model:** fetch `https://developers.openai.com/api/docs/guides/model-guidance?model=<requested-model>` through Docs MCP and extract the relevant migration section or the `## Prompting Best Practices` section through the next H2 heading. Do not substitute latest-model guidance.
|
||||||
|
|
||||||
|
Run the resolver without relying on filesystem executable bits:
|
||||||
|
|
||||||
|
- POSIX shells: `sh <skill-dir>/scripts/resolve-latest-model-info`
|
||||||
|
- Windows: run the CommonJS implementation with Node.js 18 or newer: `node <skill-dir>\scripts\resolve-latest-model-info.cjs`. If `node` is unavailable or too old and `load_workspace_dependencies` is available, use the Node.js executable it returns for this command. Do not try to execute the extensionless POSIX wrapper directly on Windows.
|
||||||
|
|
||||||
|
For the resolver branch, do not suppress or redirect its stdout. Success requires JSON containing `model`, `migrationGuideUrl`, and `promptingGuideUrl`; if the command exits without all three fields, run it once more before any fallback.
|
||||||
|
|
||||||
|
## Source Priority
|
||||||
|
|
||||||
|
- For Codex self-knowledge, use the Codex source route below; it owns when to use the manual helper, Docs MCP, or bounded uncertainty.
|
||||||
|
- For non-Codex OpenAI docs questions, use `mcp__openaiDeveloperDocs__search_openai_docs` to find the most relevant doc pages.
|
||||||
|
- For non-Codex OpenAI docs questions, fetch the relevant page with `mcp__openaiDeveloperDocs__fetch_openai_doc` before answering. If search is noisy, run a narrower Docs MCP search; when any plausible official OpenAI docs URL is known or found, try fetching that URL through Docs MCP before relying on web-search content.
|
||||||
|
- For API reference, schema, parameter, or required-field questions, use `mcp__openaiDeveloperDocs__get_openapi_spec` when available to verify the API shape alongside the relevant guide or reference page.
|
||||||
|
- Use `mcp__openaiDeveloperDocs__list_openai_docs` only when you need to browse or discover non-Codex pages without a clear query.
|
||||||
|
- For latest/current prompting guidance, model upgrades, or prompt upgrades, apply the first-action classifier above and use its platform-specific resolver command. On POSIX, the wrapper uses a compatible Node.js 18+ runtime from `$NODE`, PATH, or bundled/system fallbacks. On Windows, use a compatible Node.js executable to run the `.cjs` implementation directly. If no compatible runtime is available, call `load_workspace_dependencies` when available and retry the appropriate command once with the returned Node.js executable.
|
||||||
|
- For docs-only model-selection questions that do not ask to change an app, project, repo, model configuration, or prompts, fetch `https://developers.openai.com/api/docs/guides/latest-model.md` first. If that is unavailable, load `references/latest-model.md`.
|
||||||
|
- Preserve explicit target requests: if the user names a target model like "migrate to GPT-5.4", keep that requested target even if `latest-model.md` names a newer model. Mention newer guidance only as optional.
|
||||||
|
- If current remote guidance is needed, treat the returned migration and prompting guide URLs as opaque and fetch those exact URLs directly. Do not derive, substitute, or append a model query to them. If a prompting guide URL resolves to a combined model-guidance page, extract only the `## Prompting Best Practices` section through the next H2 heading. If a fetched guide contains only a title or no substantive body, retry the exact markdown URL through MCP/search fallback; if that also fails, use bundled fallback references and disclose the fallback.
|
||||||
|
|
||||||
|
## OpenAI product snapshots
|
||||||
|
|
||||||
|
1. Apps SDK: Build ChatGPT apps by providing a web component UI and an MCP server that exposes your app's tools to ChatGPT.
|
||||||
|
2. Responses API: A unified endpoint designed for stateful, multimodal, tool-using interactions in agentic workflows.
|
||||||
|
3. Chat Completions API: Generate a model response from a list of messages comprising a conversation.
|
||||||
|
4. Codex: OpenAI's coding agent for software development that can write, understand, review, and debug code.
|
||||||
|
5. gpt-oss: Open-weight OpenAI reasoning models (gpt-oss-120b and gpt-oss-20b) released under the Apache 2.0 license.
|
||||||
|
6. Realtime API: Build low-latency, multimodal experiences including natural speech-to-speech conversations.
|
||||||
|
7. Agents SDK: A toolkit for building agentic apps where a model can use tools and context, hand off to other agents, stream partial results, and keep a full trace.
|
||||||
|
|
||||||
|
## Codex self-knowledge
|
||||||
|
|
||||||
|
Use this path for questions about Codex itself: configuring, extending, operating, troubleshooting, local state, product surfaces, or where Codex behavior should live. A codebase merely mentioning a plugin, skill, hook, MCP server, browser, or automation is not enough. For generic software tasks, answer the software task directly; if asked whether Codex self-knowledge applies, answer that meta question briefly and continue the requested artifact.
|
||||||
|
|
||||||
|
### Source Route
|
||||||
|
|
||||||
|
The Codex manual is the first source for broad Codex synthesis. Treat the manual and Docs MCP as different lanes, not interchangeable official-doc sources. For published-user Codex product answers, the source route is complete: the manual, Docs MCP when this route calls for it, official OpenAI web fallback, and callable capabilities surfaced in the current session when the question is about that capability. Knowledge bases outside developers.openai.com are outside this route for public product answers.
|
||||||
|
|
||||||
|
For broad Codex behavior, setup, customization, skills, plugins, MCP, hooks, `AGENTS.md`, automations, surfaces, local state, or system-map questions:
|
||||||
|
|
||||||
|
1. Reuse a same-thread manual and outline path when it is still fresh.
|
||||||
|
2. Otherwise run the skill-local helper first in normal writable sessions. Skip it without trying only when the session is explicitly read-only, shell execution is unavailable, or visible policy shows no allowed temp cache.
|
||||||
|
3. By default, the helper chooses the first usable temp cache dir in this order: `$TMPDIR/openai-docs-cache`, `%TEMP%\openai-docs-cache`, `%TMP%\openai-docs-cache`, `/private/tmp/openai-docs-cache`, then `/tmp/openai-docs-cache`. Workspace-only write access is not enough for this temp cache.
|
||||||
|
4. Run the helper directly unless you need to override the cache dir. The helper falls back to `curl` when native `fetch` is unavailable or when proxy env vars are present, so no shell-specific proxy prefix is required. Resolve `<skill-dir>` to this skill's actual directory; in copied local eval workdirs this is usually `.codex/skills/openai-docs`:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
node <skill-dir>/scripts/fetch-codex-manual.mjs
|
||||||
|
```
|
||||||
|
|
||||||
|
If you need to override the cache dir, pass `--cache-dir <cache-dir>`. On Windows, the helper checks `%TEMP%` and `%TMP%` automatically; in PowerShell, `$env:TEMP\\openai-docs-cache` is a typical explicit override.
|
||||||
|
|
||||||
|
Treat helper availability as established by explicit read-only/no-shell policy or an actual command result. A guessed sandbox or guessed helper failure is not enough to switch to Docs MCP or web lookup; after an actual helper command failure, continue to the narrowest official next source below.
|
||||||
|
|
||||||
|
The helper verifies freshness, writes `codex-manual.md`, and emits `codex-manual.outline.md`. The outline maps source pages and headings to line ranges; use it to choose the relevant manual section, then read or search targeted manual sections for Codex product facts. Use the skill directory to locate and run the helper; after the helper succeeds, use the returned manual and outline paths as the search scope for Codex product facts and term coverage checks.
|
||||||
|
|
||||||
|
Reuse the same-thread manual and outline paths for follow-up Codex questions. Refresh first when the manual was fetched more than about a day ago, the path is unusable, the path came from another thread or uncertain provenance, or likely-current information is missing and staleness is plausible.
|
||||||
|
|
||||||
|
For questions about whether the manual is current enough to rely on now, run the helper when temp caching is allowed and base the answer on its returned status, manual path, and outline path.
|
||||||
|
|
||||||
|
If the manual resolves a Codex claim, answer from it and stop expanding sources for that claim; continue the user's broader task if the docs lookup was only one dependency. Manual source pages and known anchors are enough citation support for manual-covered material.
|
||||||
|
|
||||||
|
If the helper is skipped because the session is read-only, has no shell execution, or has no allowed temp cache, the next source is Docs MCP: call `mcp__openaiDeveloperDocs__search_openai_docs`, then `mcp__openaiDeveloperDocs__fetch_openai_doc` for a relevant hit before any web fallback.
|
||||||
|
|
||||||
|
If a user names a Codex term or mode that a fresh manual does not use, search the manual for obvious adjacent concepts, then answer that the exact term is not documented and use the closest documented terminology. If the prompt asks how that term maps to Codex behavior, resolve the mapping from adjacent manual sections. If the exact term remains material or likely current after that manual pass, use one narrow Docs MCP search/fetch before bounded uncertainty; otherwise, the source lookup for that terminology or mapping claim is complete.
|
||||||
|
|
||||||
|
Use the narrowest official next source only when the manual is unavailable, the helper fails, temp caching is not allowed, another material claim is missing or likely stale, or the user explicitly needs a page-specific citation. Prefer one specific Docs MCP search and, if it returns a clearly relevant page, one fetch; for unresolved Codex capability names, acronyms, scheduling terms, or exact error text, this Docs MCP step is the next source before web search. After the manual plus any permitted Docs MCP gap-fill, resolve remaining gaps as bounded uncertainty. Use official-domain web fallback only after that Docs MCP path is unavailable or unhelpful. If the claim is still not established, stop with bounded uncertainty. If official docs/manual conflict with a callable capability already surfaced in the current session, state the conflict and prefer verified current-session behavior for that environment.
|
||||||
|
|
||||||
|
For undocumented or private-looking model slugs, product mode labels, entitlement labels, account access paths, or rollout names, answer from current public docs and bounded uncertainty. Those labels are not a reason to leave the public source route.
|
||||||
|
|
||||||
|
For support-style diagnostics, prefer a layer-by-layer answer from the manual over provider-specific web lookups: installed/enabled plugin, bundled app or connector authorization, MCP setup, workspace/admin policy, restart or new-thread expectations, then support or feedback if still unresolved.
|
||||||
|
|
||||||
|
If the source route still does not establish a claim, return bounded uncertainty or route to support, an admin, or product feedback instead of widening the investigation.
|
||||||
|
|
||||||
|
For unresolved product terminology, answer from the manual plus the allowed official next source. If those sources do not establish the term, answer with bounded uncertainty from those sources.
|
||||||
|
|
||||||
|
### Surface Map
|
||||||
|
|
||||||
|
When Codex nouns or durable-instruction surfaces overlap, recommend the smallest surface that matches the scope:
|
||||||
|
|
||||||
|
- Prompt or thread context -> one-off task constraints.
|
||||||
|
- `AGENTS.md` -> durable repo conventions, commands, verification steps, and review expectations; closer nested files apply under their subtree.
|
||||||
|
- Project `.codex/config.toml` -> trusted-repo Codex settings such as sandbox, MCP, hooks, model, or reasoning defaults.
|
||||||
|
- Global config or global guidance -> personal defaults across repos.
|
||||||
|
- Skill -> reusable task workflow with references or scripts.
|
||||||
|
- Plugin -> installable bundle with skills plus commands, tools, MCP config, hooks, assets, apps, or marketplace metadata.
|
||||||
|
- MCP server or app connector -> live external data/actions or authorized private app/workspace data. Use connectors for private Google Docs, Calendar, Slack, GitHub, Notion, and similar data instead of web search or model memory.
|
||||||
|
- Automation -> scheduled checks, reminders, monitors, or follow-up work; use a thread heartbeat when continuity in an existing thread matters.
|
||||||
|
- Hook -> lifecycle enforcement around tool calls, commands, or file edits.
|
||||||
|
|
||||||
|
Split mixed-scope requests instead of forcing one answer. Example: "always do X, but only for this PR" defaults to prompt/thread context for the current run; use `AGENTS.md` or project config only if it should persist, hooks only for mechanical enforcement, and automations only for scheduled or follow-up work.
|
||||||
|
|
||||||
|
Use this quick product map when needed: CLI is terminal-first local repo work; IDE extension is editor-attached coding; Codex app is desktop planning, review, and interactive work; cloud/web is hosted parallel/offloaded work; Browser Use/in-app browser is Codex-controlled web testing; Chrome extension uses the user's Chrome profile; Computer Use controls desktop apps and OS UI. Keep `config.toml` defaults, `requirements.toml` constraints, and managed/admin policy separate.
|
||||||
|
|
||||||
|
### Boundaries And Output
|
||||||
|
|
||||||
|
- API key auth does not imply ChatGPT, cloud task, or connector access. For plugin/app/auth failures, check bundle availability, plugin installed/enabled state, connector/app authorization, MCP setup, restart/refresh expectations, workspace policy, and per-surface availability before answering.
|
||||||
|
- Sandbox or network denials need scoped escalation with a clear justification. Destructive commands, writes outside the workspace, or broad access changes require explicit approval.
|
||||||
|
- Memory can provide user preference or context, but explicit prompt instructions win and memory is not a source for current external facts.
|
||||||
|
- For affirmative surface-selection answers, use this shape: recommendation, why, what to avoid, and the manual/source evidence used.
|
||||||
|
- When page-specific Codex citations are actually needed, these anchors often fit: `concepts/customization#agents-guidance` for `AGENTS.md`, `concepts/customization#skills` for skills, `plugins/build#plugin-structure` for plugins, `concepts/customization#mcp` for MCP, `config-advanced#hooks` for hooks, `app/automations#thread-automations` for thread automations, and `config-reference#configtoml` for config.
|
||||||
|
|
||||||
|
## If MCP server is missing
|
||||||
|
|
||||||
|
If MCP tools fail or no OpenAI docs resources are available:
|
||||||
|
|
||||||
|
1. Run the install command yourself: `codex mcp add openaiDeveloperDocs --url https://developers.openai.com/mcp`
|
||||||
|
2. If it fails due to permissions/sandboxing, immediately retry the same command with escalated permissions and include a 1-sentence justification for approval.
|
||||||
|
3. Ask the user to run the install command only if the escalated attempt fails.
|
||||||
|
4. Ask the user to restart Codex.
|
||||||
|
5. Re-run the doc search/fetch after restart.
|
||||||
|
|
||||||
|
## Workflow
|
||||||
|
|
||||||
|
1. Clarify whether the request is general docs lookup, model selection, a model-string upgrade, prompt-upgrade guidance, or broader API/provider migration.
|
||||||
|
2. For Codex self-knowledge requests, follow the Codex self-knowledge source procedure above.
|
||||||
|
3. For model-selection or upgrade requests, prefer current remote docs over bundled references when the user asks for latest/current/default guidance.
|
||||||
|
- For docs-only model-selection questions, fetch `https://developers.openai.com/api/docs/guides/latest-model.md`, find the latest model ID and explicit migration or prompt-guidance links, and prefer explicit links over derived URLs.
|
||||||
|
- For explicit named-model requests, preserve the requested model target. Mention newer remote guidance only as optional.
|
||||||
|
- For latest/current/default prompting guidance or dynamic upgrades, run the resolver with the platform-specific command above as the first docs operation before any direct latest-model.md fetch or API-key credential gate, then fetch both returned guide URLs directly when possible.
|
||||||
|
- Fetch returned guide URLs exactly; do not derive or substitute model-specific URLs.
|
||||||
|
- If a direct guide fetch fails or returns only a title, use the developer-docs MCP tools or official OpenAI-domain search to find the same guide content.
|
||||||
|
- If remote docs are unavailable, use bundled fallback references and say that fallback guidance was used.
|
||||||
|
4. For model upgrades, keep changes behavior-preserving and scoped: update active OpenAI API model defaults, directly related prompts, and the registries, routing, pricing, capability, or picker surfaces that the user actually placed in scope.
|
||||||
|
5. Leave historical docs, examples, eval baselines, fixtures, provider comparisons, intentionally pinned fallbacks, and ambiguous older model usage unchanged unless the user explicitly asks to upgrade them. Do not collapse a multi-model router or picker into one flagship model; preserve the existing cost, latency, and quality roles.
|
||||||
|
6. Keep SDK, tooling, IDE, plugin, shell, auth, and provider-environment migrations out of a model-and-prompt upgrade unless the user explicitly asks for them.
|
||||||
|
7. If a safe upgrade needs API-surface changes, schema rewiring, tool-handler changes, or broader implementation work, classify it explicitly. Make those changes when implementation is within the user's requested scope; otherwise report the exact blocker or confirmation needed instead of silently changing behavior.
|
||||||
|
8. For general docs lookup, start with a compact, title-like search query of 2-6 essential terms. Do not turn the full user question into a keyword list. Fetch the best page and exact section needed, and answer with concise citations.
|
||||||
|
|
||||||
|
## Reference map
|
||||||
|
|
||||||
|
Read only what you need:
|
||||||
|
|
||||||
|
- `https://developers.openai.com/api/docs/guides/latest-model.md` -> current model-selection and "best/latest/current model" questions.
|
||||||
|
- `scripts/fetch-codex-manual.mjs` -> current Codex manual fetch, verification, local temp cache, and outline generation.
|
||||||
|
- `https://developers.openai.com/codex/codex-manual.md` -> current Codex self-knowledge synthesis, including setup, customization, skills, plugins, MCP, hooks, `AGENTS.md`, automations, and surface behavior; normally access it through the helper path and targeted file reads when temp caching is available.
|
||||||
|
- `references/latest-model.md` -> bundled fallback for model-selection and "best/latest/current model" questions.
|
||||||
|
- `references/upgrade-guide.md` -> bundled routing fallback for model upgrade and upgrade-planning requests.
|
||||||
|
- `references/upgrading-to-gpt-5p6-sol.md` -> GPT-5.6 Sol/family migration judgment, compatibility gates, optional feature boundaries, and validation.
|
||||||
|
- `references/prompting-guide.md` -> bundled GPT-5.6 prompting fallback plus the live Prompting Best Practices extraction contract.
|
||||||
|
|
||||||
|
## Quality rules
|
||||||
|
|
||||||
|
- Treat OpenAI docs as the source of truth; avoid speculation.
|
||||||
|
- For Codex self-knowledge, follow the source route above instead of relying on remembered behavior.
|
||||||
|
- Keep migration changes narrow and behavior-preserving.
|
||||||
|
- Prefer prompt-only upgrades when possible.
|
||||||
|
- Avoid inventing pricing, availability, parameters, API changes, or breaking changes.
|
||||||
|
- Keep quotes short and within policy limits; prefer paraphrase with citations.
|
||||||
|
- If multiple pages differ, call out the difference and cite both.
|
||||||
|
- If official docs and verified callable current-session behavior disagree, state the conflict before making broad claims or edits.
|
||||||
|
- If docs do not cover the user’s need, say so and offer next steps.
|
||||||
|
|
||||||
|
## Tooling notes
|
||||||
|
|
||||||
|
- Use MCP doc tools before web search for OpenAI-related markdown docs. The Codex manual flow is the exception: follow the Codex self-knowledge source procedure for broad Codex synthesis.
|
||||||
|
- If the MCP server is installed but returns no meaningful results, then use web search as a fallback.
|
||||||
|
- When falling back to web search, restrict to official OpenAI domains (developers.openai.com, platform.openai.com) and cite sources.
|
||||||
14
skills/.system/openai-docs/agents/openai.yaml
Normal file
14
skills/.system/openai-docs/agents/openai.yaml
Normal file
@ -0,0 +1,14 @@
|
|||||||
|
interface:
|
||||||
|
display_name: "OpenAI Docs"
|
||||||
|
short_description: "Reference OpenAI docs, Codex self-knowledge, and model migration guidance"
|
||||||
|
icon_small: "./assets/openai-small.svg"
|
||||||
|
icon_large: "./assets/openai.png"
|
||||||
|
default_prompt: "Use OpenAI Docs for official docs lookup, questions about Codex itself or Codex surfaces, model selection, model migration, and prompt-upgrade work."
|
||||||
|
|
||||||
|
dependencies:
|
||||||
|
tools:
|
||||||
|
- type: "mcp"
|
||||||
|
value: "openaiDeveloperDocs"
|
||||||
|
description: "OpenAI Developer Docs MCP server"
|
||||||
|
transport: "streamable_http"
|
||||||
|
url: "https://developers.openai.com/mcp"
|
||||||
3
skills/.system/openai-docs/assets/openai-small.svg
Normal file
3
skills/.system/openai-docs/assets/openai-small.svg
Normal file
@ -0,0 +1,3 @@
|
|||||||
|
<svg xmlns="http://www.w3.org/2000/svg" width="14" height="14" fill="currentColor" viewBox="0 0 14 14">
|
||||||
|
<path d="M10.931 3.34a.112.112 0 0 0-.069-.104l-.038-.007c-1.537.05-2.45.318-3.714 1.002v6.683c.48-.248.936-.44 1.414-.58.695-.203 1.417-.292 2.303-.305l.038-.008a.113.113 0 0 0 .066-.104V3.341ZM2.363 9.919c0 .064.051.11.105.111l.33.008c1.162.046 2.042.243 2.975.662-.403-.585-1.008-1.075-1.654-1.292a.991.991 0 0 1-.674-.941v-5.14a6.36 6.36 0 0 0-.59-.076l-.37-.02a.115.115 0 0 0-.122.111v6.577Zm9.455-.001a.998.998 0 0 1-.877.992l-.101.007c-.832.012-1.47.095-2.066.27-.599.174-1.176.448-1.883.863a.444.444 0 0 1-.449 0c-1.299-.763-2.229-1.07-3.689-1.125l-.299-.008a.997.997 0 0 1-.977-.998V3.342c0-.573.478-1.017 1.038-.999l.417.023c.188.015.35.037.513.062v-.754c0-.708.749-1.244 1.429-.903.984.492 1.836 1.449 2.15 2.505 1.216-.617 2.222-.884 3.771-.934l.105.003a.998.998 0 0 1 .918.996v6.576ZM4.332 8.466c0 .049.03.087.07.1l.24.091a4.319 4.319 0 0 1 1.581 1.176V3.721c-.164-.803-.799-1.617-1.584-2.07l-.162-.088c-.025-.012-.054-.013-.088.009a.12.12 0 0 0-.057.102v6.792Z"/>
|
||||||
|
</svg>
|
||||||
|
After Width: | Height: | Size: 1.1 KiB |
BIN
skills/.system/openai-docs/assets/openai.png
Normal file
BIN
skills/.system/openai-docs/assets/openai.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 1.4 KiB |
40
skills/.system/openai-docs/references/latest-model.md
Normal file
40
skills/.system/openai-docs/references/latest-model.md
Normal file
@ -0,0 +1,40 @@
|
|||||||
|
# Latest model guide
|
||||||
|
|
||||||
|
This file is a curated helper. Every recommendation here must be verified against current OpenAI docs before it is repeated to a user.
|
||||||
|
|
||||||
|
## Current model map
|
||||||
|
|
||||||
|
| Model ID | Use for |
|
||||||
|
| --- | --- |
|
||||||
|
| `gpt-5.6` | Latest/default GPT-5.6 alias; routes to Sol |
|
||||||
|
| `gpt-5.6-sol` | Flagship GPT-5.6 tier for hardest quality-first, coding, and reasoning workflows |
|
||||||
|
| `gpt-5.6-terra` | Mini-like GPT-5.6 tier for balanced cost, latency, and quality |
|
||||||
|
| `gpt-5.6-luna` | Nano-like GPT-5.6 tier for high-throughput, simple, or strict-latency tasks |
|
||||||
|
| `gpt-5.5` | Previous default text and reasoning model; use for existing GPT-5.5 integrations |
|
||||||
|
| `gpt-5.4` | Older default text and reasoning model; use for existing GPT-5.4 integrations |
|
||||||
|
| `gpt-5.4-mini` | Older lower-cost testing and lighter production workflows |
|
||||||
|
| `gpt-5.4-nano` | Older high-throughput simple tasks and classification |
|
||||||
|
| `gpt-4.1-mini` | Cheaper no-reasoning text |
|
||||||
|
| `gpt-4.1-nano` | Fastest and cheapest no-reasoning text |
|
||||||
|
| `gpt-5.3-codex` | Agentic coding, code editing, and tool-heavy coding workflows |
|
||||||
|
| `gpt-5.1-codex-mini` | Cheaper coding workflows |
|
||||||
|
| `gpt-image-2` | Best image generation and edit quality |
|
||||||
|
| `gpt-image-1.5` | Less expensive image generation and edit quality |
|
||||||
|
| `gpt-image-1-mini` | Cost-optimized image generation |
|
||||||
|
| `gpt-4o-mini-tts` | Text-to-speech |
|
||||||
|
| `gpt-4o-mini-transcribe` | Speech-to-text, fast and cost-efficient |
|
||||||
|
| `gpt-realtime-1.5` | Realtime voice and multimodal sessions |
|
||||||
|
| `gpt-realtime-mini` | Cheaper realtime sessions |
|
||||||
|
| `gpt-audio` | Chat Completions audio input and output |
|
||||||
|
| `gpt-audio-mini` | Cheaper Chat Completions audio workflows |
|
||||||
|
| `sora-2` | Faster iteration and draft video generation |
|
||||||
|
| `sora-2-pro` | Higher-quality production video |
|
||||||
|
| `omni-moderation-latest` | Text and image moderation |
|
||||||
|
| `text-embedding-3-large` | Higher-quality retrieval embeddings; default in this skill because no best-specific row exists |
|
||||||
|
| `text-embedding-3-small` | Lower-cost embeddings |
|
||||||
|
|
||||||
|
## Maintenance notes
|
||||||
|
|
||||||
|
- GPT-5.6 Pro is a Responses reasoning mode on the base model, not a separate `gpt-5.6-pro` slug. Verify the live model guide before recommending its request shape.
|
||||||
|
- This file will drift unless it is periodically re-verified against current OpenAI docs.
|
||||||
|
- If this file conflicts with current docs, the docs win.
|
||||||
297
skills/.system/openai-docs/references/prompting-guide.md
Normal file
297
skills/.system/openai-docs/references/prompting-guide.md
Normal file
@ -0,0 +1,297 @@
|
|||||||
|
## Retrieve the live GPT-5.6 prompting guidance
|
||||||
|
|
||||||
|
Use the OpenAI Docs MCP to fetch the live GPT-5.6 prompting guidance from:
|
||||||
|
|
||||||
|
https://developers.openai.com/api/docs/guides/model-guidance?model=gpt-5.6#prompting-best-practices
|
||||||
|
|
||||||
|
Read only the `## Prompting Best Practices` section, stopping at the next H2 heading. The URL anchor points to the section visually, but the Docs MCP may return the full page, so explicitly extract only that section.
|
||||||
|
|
||||||
|
Treat the live section as the canonical model-specific prompting guidance. Use the local guidance below only for skill-specific migration judgment: deciding what to preserve, remove, rewrite, or test when adapting an existing prompt stack to GPT-5.6.
|
||||||
|
|
||||||
|
## Skill-specific migration judgment
|
||||||
|
|
||||||
|
GPT-5.6 works best when prompts define the outcome, important constraints, available evidence, and completion bar, then leave room for the model to choose an efficient path.
|
||||||
|
|
||||||
|
Removing repeated instructions and examples and simplifying tool descriptions can improve task performance and token efficiency. In a sample of internal coding-agent eval runs, configurations with leaner system prompts improved evaluation scores by roughly 10–15% while reducing total tokens by 41–66% and cost by 33–67%. Results will vary by workload, so treat these ranges as directional and validate changes on representative tasks from your own application.
|
||||||
|
|
||||||
|
## Simplify prompts first
|
||||||
|
|
||||||
|
Start with a prompt and tool set that already works. Remove one group of instructions, examples, or tools at a time, then rerun the same evals.
|
||||||
|
|
||||||
|
Trim:
|
||||||
|
|
||||||
|
- repeated statements of the same rule;
|
||||||
|
- repeated style or process instructions that do not change behavior;
|
||||||
|
- examples that do not change behavior;
|
||||||
|
- process instructions for behavior the model already performs reliably;
|
||||||
|
- tools and tool descriptions unrelated to the task.
|
||||||
|
|
||||||
|
Keep:
|
||||||
|
|
||||||
|
- the user-visible outcome;
|
||||||
|
- success criteria and stopping conditions;
|
||||||
|
- safety, business, evidence, and permission constraints;
|
||||||
|
- tool-routing rules when the route depends on context;
|
||||||
|
- required output shape and validation requirements.
|
||||||
|
|
||||||
|
Review the remaining instructions for contradictions. GPT-5-class models follow prompt contracts closely, so conflicting rules can create more instability than missing detail.
|
||||||
|
|
||||||
|
## Outcome-first prompts and stopping conditions
|
||||||
|
|
||||||
|
Describe the destination rather than prescribing every step. GPT-5.6 can usually choose an efficient search, tool, or reasoning path when the prompt states what good looks like.
|
||||||
|
|
||||||
|
Prefer:
|
||||||
|
|
||||||
|
Resolve the customer's issue end to end.
|
||||||
|
|
||||||
|
Success means:
|
||||||
|
- make the eligibility decision from available policy and account evidence
|
||||||
|
- complete any allowed action before responding
|
||||||
|
- return completed_actions, customer_message, and blockers
|
||||||
|
- if required evidence is missing, ask for the smallest missing field
|
||||||
|
|
||||||
|
Avoid unnecessary absolute rules. Use ALWAYS, NEVER, must, and only for true invariants such as safety rules, required fields, or actions that should never happen. For judgment calls, such as when to search, ask, use a tool, or keep iterating, prefer decision rules.
|
||||||
|
|
||||||
|
Preserve explicit user values. When the correct value is implicit, provide decision criteria and let the model reason from context or schema. Avoid universal defaults, keyword maps, and broad semantic shortcuts.
|
||||||
|
|
||||||
|
Add stopping conditions:
|
||||||
|
|
||||||
|
Resolve the request in the fewest useful tool loops, but do not let loop
|
||||||
|
minimization outrank correctness, required evidence, calculations, or
|
||||||
|
required citations.
|
||||||
|
|
||||||
|
After each result, ask whether the core request can now be answered with
|
||||||
|
useful evidence. If yes, answer. If required evidence is still missing,
|
||||||
|
name the missing fact and use the smallest useful fallback.
|
||||||
|
|
||||||
|
## Personality, collaboration, and response length
|
||||||
|
|
||||||
|
GPT-5.6 tends to be more concise by default than GPT-5.5. When migrating, check whether broad brevity instructions such as “Be concise” or “Keep it short” are still useful. They may be unnecessary for some tasks and can sometimes make responses too brief. Keep them when they reliably produce the output your application needs.
|
||||||
|
|
||||||
|
For more consistent control across requests, use `text.verbosity` to set the default level of detail, then use the prompt for task-specific requirements. Choose `low`, `medium`, or `high` as the default level of detail for a request. In the prompt, specify any task-specific length, structure, or required content. See [Set up `text.verbosity`](https://developers.openai.com/api/docs/guides/deployment-checklist#set-up-textverbosity) for an API example.
|
||||||
|
|
||||||
|
For customer-facing assistants and collaborative products, define both personality and collaboration style.
|
||||||
|
|
||||||
|
- Personality controls tone, warmth, directness, formality, humor, empathy, and polish.
|
||||||
|
- Collaboration style controls when the model asks questions, makes assumptions, takes initiative, explains tradeoffs, checks work, and handles uncertainty.
|
||||||
|
|
||||||
|
Keep both short. Personality should shape the user experience; collaboration instructions should shape task behavior. Neither should replace clear goals, success criteria, tool rules, or stopping conditions.
|
||||||
|
|
||||||
|
When a task calls for a shorter answer, identify the information the model must preserve and the detail it can omit. For example:
|
||||||
|
|
||||||
|
Lead with the conclusion. Include the evidence needed to support it, any material
|
||||||
|
caveat, and the next action. Omit secondary detail and repetition.
|
||||||
|
|
||||||
|
Keep all required facts, decisions, caveats, and next steps. Trim introductions,
|
||||||
|
repetition, generic reassurance, and optional background first.
|
||||||
|
|
||||||
|
This gives the model a clear priority order: preserve the content needed to complete the task, then remove lower-value detail.
|
||||||
|
|
||||||
|
Broad labels such as “friendly” or “empathetic” can be ambiguous. Describe the writing choices that define your product's tone, such as how directly to state the answer, when to acknowledge a problem, and whether reassurance or a sign-off is appropriate.
|
||||||
|
|
||||||
|
State the answer directly. If the user reports a problem, acknowledge the
|
||||||
|
specific issue before giving the next step. Use reassurance only when it is
|
||||||
|
relevant. Omit generic praise and unnecessary sign-offs.
|
||||||
|
|
||||||
|
Avoid blanket language rules such as “always respond in the user's language” unless that is truly the product requirement. Specify the intended output language and when it should change.
|
||||||
|
|
||||||
|
For editing, rewriting, summaries, and customer-facing drafts, tell the model what to preserve:
|
||||||
|
|
||||||
|
Preserve the requested artifact, length, structure, genre, and factual claims
|
||||||
|
first. Improve clarity, flow, and correctness without adding new claims,
|
||||||
|
sections, or a more promotional tone unless requested.
|
||||||
|
|
||||||
|
## Define autonomy and approval boundaries
|
||||||
|
|
||||||
|
GPT-5.6 can be proactive and persistent when carrying out multi-step tasks. Define what level of action each request authorizes so the model can continue safe, in-scope work without unnecessary pauses while stopping before external, destructive, costly, or scope-expanding actions.
|
||||||
|
|
||||||
|
A compact policy is usually sufficient:
|
||||||
|
|
||||||
|
For requests to answer, explain, review, diagnose, or plan, inspect the
|
||||||
|
relevant materials and report the result. Do not implement changes unless
|
||||||
|
the request also asks for them.
|
||||||
|
|
||||||
|
For requests to change, build, or fix, make the requested in-scope local
|
||||||
|
changes and run relevant non-destructive validation without asking first.
|
||||||
|
|
||||||
|
Require confirmation for external writes, destructive actions, purchases,
|
||||||
|
or a material expansion of scope.
|
||||||
|
|
||||||
|
Name safe local actions explicitly, such as reading files, inspecting logs, editing in-scope code, and running tests. Keep the policy in one place and state each rule once. Repeating instructions such as “ask first,” “do not mutate,” or “wait for approval” can cause unnecessary approval requests for safe, expected actions.
|
||||||
|
|
||||||
|
For long-running work, define the current layer of work. Distinguish research, design, implementation, review, and external coordination so the model does not silently move from one layer to another.
|
||||||
|
|
||||||
|
## Tool routing
|
||||||
|
|
||||||
|
Expose only task-relevant tools. Tool descriptions should state what the tool does, when to use it, important return fields, and error behavior.
|
||||||
|
|
||||||
|
When correctness depends on prerequisite retrieval or lookup, say so:
|
||||||
|
|
||||||
|
Before taking an action, resolve required discovery, retrieval, and
|
||||||
|
validation steps. Do not skip a prerequisite because the intended final
|
||||||
|
state seems obvious.
|
||||||
|
|
||||||
|
When several reads are independent, parallelize them. When one result determines the next action, keep the work sequential. After parallel retrieval, synthesize before acting.
|
||||||
|
|
||||||
|
If a tool returns empty, partial, or suspiciously narrow results, try one or two meaningful fallbacks before concluding that no result exists.
|
||||||
|
|
||||||
|
## Programmatic Tool Calling
|
||||||
|
|
||||||
|
Programmatic Tool Calling (PTC) works best for bounded workflows where code can process several tool results or large intermediate outputs and return a much smaller structured result.
|
||||||
|
|
||||||
|
Multiple, parallel, or dependent calls alone do not justify Programmatic Tool Calling.
|
||||||
|
|
||||||
|
Use it for:
|
||||||
|
|
||||||
|
- filtering, joining, sorting, ranking, deduplication, and aggregation;
|
||||||
|
- batching across many similar records;
|
||||||
|
- repeated deterministic validation;
|
||||||
|
- large structured results that can be reduced to a compact schema.
|
||||||
|
|
||||||
|
Prefer direct tool calls when:
|
||||||
|
|
||||||
|
- one call is sufficient;
|
||||||
|
- intermediate outputs are already small;
|
||||||
|
- each result may change the next decision;
|
||||||
|
- an action requires approval;
|
||||||
|
- the final answer must preserve citations or native artifacts;
|
||||||
|
- the workflow requires semantic judgment between calls.
|
||||||
|
|
||||||
|
Do not rely on generic instructions such as “use Programmatic Tool Calling efficiently.” State the bounded stage, eligible tools, output schema, retry limit, stop condition, and handoff back to direct model judgment.
|
||||||
|
|
||||||
|
Use Programmatic Tool Calling only for the bounded record-reduction stage.
|
||||||
|
Call only the documented read-only tools. Filter and deduplicate the
|
||||||
|
intermediate results, then emit exactly the required compact schema with
|
||||||
|
evidence fields. Retry transient failures at most twice. Use direct tool
|
||||||
|
calls for approval, semantic judgment, citations, and final validation.
|
||||||
|
|
||||||
|
If both routes are needed, define one clear handoff and tell the model not to switch routes or repeat completed work.
|
||||||
|
|
||||||
|
The `program_output` item and final assistant `message` are separate outputs; make sure to test both. In theory, a program can return the correct records while the message omits a required field, citation, or caveat.
|
||||||
|
|
||||||
|
Compare direct and programmatic calling on the same representative tasks. Check whether the final response is correct, complete, and includes the required evidence. Then compare total tokens, latency, cost, calls, turns, and retries. Count lower resource use as an improvement only when the response still passes your existing evals.
|
||||||
|
|
||||||
|
## Grounding, citations, and retrieval budgets
|
||||||
|
|
||||||
|
For grounded answers, citation behavior should be part of the prompt. Define what needs support, what counts as enough evidence, and how to behave when evidence is missing. Absence of evidence should not automatically become a factual “no.”
|
||||||
|
|
||||||
|
For ordinary Q&A, start with one broad search using short, discriminative
|
||||||
|
keywords. If the top results contain enough support for the core request,
|
||||||
|
answer from those results.
|
||||||
|
|
||||||
|
Make another retrieval call only when a required fact, owner, date, ID, or
|
||||||
|
source is missing; the user asked for exhaustive coverage or comparison; a
|
||||||
|
specific artifact must be read; or an important claim would otherwise be
|
||||||
|
unsupported.
|
||||||
|
|
||||||
|
Do not search again only to improve phrasing, add examples, or support
|
||||||
|
nonessential detail.
|
||||||
|
|
||||||
|
For research and synthesis:
|
||||||
|
|
||||||
|
- cite only retrieved sources;
|
||||||
|
- attach citations to the claims they support;
|
||||||
|
- label inference separately from directly supported facts;
|
||||||
|
- state conflicts between sources;
|
||||||
|
- narrow the answer or report missing evidence instead of guessing.
|
||||||
|
|
||||||
|
For creative drafting, distinguish source-backed facts from creative wording. Do not invent names, metrics, dates, roadmap status, customer outcomes, or product capabilities to make a draft sound stronger.
|
||||||
|
|
||||||
|
## Long-running workflows and state
|
||||||
|
|
||||||
|
For multi-step or tool-heavy tasks, prompt for a short visible preamble before the first tool call, then sparse outcome-based updates at major phase changes. Do not ask the model to narrate routine tool calls.
|
||||||
|
|
||||||
|
Before tool calls for a multi-step task, send a one- or two-sentence
|
||||||
|
user-visible update that states the first step. During the task, update only
|
||||||
|
when a major phase begins or a finding changes the plan. Each update should
|
||||||
|
state one concrete outcome and the next step.
|
||||||
|
|
||||||
|
Preserve assistant phase values when replaying history so the model can distinguish commentary from the final answer. If using previous_response_id, prior assistant state is preserved automatically. If replaying history manually, preserve each original phase value unchanged.
|
||||||
|
|
||||||
|
Compact after major milestones rather than every turn. Keep the prompt functionally consistent after compaction and treat compacted items as opaque state.
|
||||||
|
|
||||||
|
Persisted reasoning is useful when the objective, assumptions, and priorities remain stable across turns. Use current-turn behavior when earlier reasoning is no longer relevant. Do not treat persisted reasoning as an always-on optimization: stale reasoning can add tokens, increase latency, and anchor the model to an outdated approach.
|
||||||
|
|
||||||
|
Prompt caching also affects prompt construction. Keep reusable prefixes stable and avoid unnecessary churn in large system prompts. Use explicit cache breakpoints only when they improve measured cache behavior and cost for the workload.
|
||||||
|
|
||||||
|
## Reasoning effort
|
||||||
|
|
||||||
|
Establish a baseline with the current reasoning effort before changing it.
|
||||||
|
|
||||||
|
- Preserve the current GPT-5.5 or GPT-5.4 reasoning effort as the baseline.
|
||||||
|
- Test the same setting and one level lower on representative tasks.
|
||||||
|
- Use low for latency-sensitive work when it preserves quality.
|
||||||
|
- Use medium as a balanced starting point.
|
||||||
|
- Use high or xhigh only when evals show a meaningful gain.
|
||||||
|
- Reserve max for the hardest quality-first workloads; do not recommend it globally.
|
||||||
|
|
||||||
|
Before increasing reasoning effort, check whether the prompt is missing a success criterion, dependency rule, tool-routing rule, or verification loop.
|
||||||
|
|
||||||
|
## Frontend and visual tasks
|
||||||
|
|
||||||
|
GPT-5.6 has stronger layout, visual hierarchy, and design judgment. Still provide product context, preserve the existing design system, and name the states and constraints that matter.
|
||||||
|
|
||||||
|
For incremental frontend changes:
|
||||||
|
|
||||||
|
- inspect and preserve existing design tokens, components, and patterns;
|
||||||
|
- do not add extra features or decorative UI unless requested;
|
||||||
|
- preserve responsive behavior and expected states;
|
||||||
|
- render and inspect the result before finalizing.
|
||||||
|
|
||||||
|
For vision, computer use, localization, or OCR tasks where spatial precision matters, choose image detail intentionally. Use original detail for large, dense, or coordinate-sensitive images when the extra input cost and latency are justified.
|
||||||
|
|
||||||
|
## Check work before finishing
|
||||||
|
|
||||||
|
Give GPT-5.6 access to tools that can validate the output, and state what validation matters.
|
||||||
|
|
||||||
|
For coding:
|
||||||
|
|
||||||
|
After making changes, run the most relevant validation available:
|
||||||
|
- targeted tests for changed behavior
|
||||||
|
- type checks or lint checks when applicable
|
||||||
|
- build checks for affected packages
|
||||||
|
- a minimal smoke test when full validation is too expensive
|
||||||
|
|
||||||
|
If validation cannot be run, explain why and describe the next best check.
|
||||||
|
|
||||||
|
For visual artifacts:
|
||||||
|
|
||||||
|
Render the artifact before finalizing. Inspect layout, clipping, spacing,
|
||||||
|
missing content, and visual consistency. Revise until the rendered output
|
||||||
|
matches the requirements.
|
||||||
|
|
||||||
|
For implementation plans, include requirements, named resources or files, state transitions or data flow, validation checks, failure behavior, privacy or security considerations, and open questions that materially affect implementation.
|
||||||
|
|
||||||
|
## Suggested prompt structure
|
||||||
|
|
||||||
|
Use this structure as a starting point for complex prompts. Keep each section short. Add detail only where it changes behavior.
|
||||||
|
|
||||||
|
Role: [the model's function and context]
|
||||||
|
|
||||||
|
Personality: [tone and collaboration style]
|
||||||
|
|
||||||
|
Goal: [user-visible outcome]
|
||||||
|
|
||||||
|
Success criteria: [what must be true before the final answer]
|
||||||
|
|
||||||
|
Constraints: [policy, safety, business, evidence, and side-effect limits]
|
||||||
|
|
||||||
|
Tools: [which tools to use, when, and what not to use]
|
||||||
|
|
||||||
|
Output: [sections, length, format, and tone]
|
||||||
|
|
||||||
|
Stop rules: [when to retry, fallback, abstain, ask, or stop]
|
||||||
|
|
||||||
|
## Prompt migration workflow
|
||||||
|
|
||||||
|
When moving an existing application to GPT-5.6:
|
||||||
|
|
||||||
|
1. Switch the model and preserve the current reasoning effort.
|
||||||
|
2. Run representative evals before changing the prompt.
|
||||||
|
3. Remove obsolete scaffolding, repeated instructions, and irrelevant tools.
|
||||||
|
4. Add only the smallest targeted instruction that fixes a measured regression.
|
||||||
|
5. Re-run evals after each prompt or reasoning change.
|
||||||
|
|
||||||
|
Do not rewrite a working prompt stack all at once. Otherwise you cannot tell whether a behavior change came from the model, reasoning setting, prompt, tool set, or runtime.
|
||||||
|
|
||||||
|
When a prompt regresses, debug it with a small set of real traces. Identify the failure mode, find the instruction or contradiction that likely caused it, make a surgical edit, and rerun the same cases.
|
||||||
22
skills/.system/openai-docs/references/upgrade-guide.md
Normal file
22
skills/.system/openai-docs/references/upgrade-guide.md
Normal file
@ -0,0 +1,22 @@
|
|||||||
|
# Model upgrade guidance
|
||||||
|
|
||||||
|
Use this file only as a bundled routing fallback when the live migration guide cannot be fetched.
|
||||||
|
|
||||||
|
For latest, current, default, or unspecified-model upgrades:
|
||||||
|
|
||||||
|
1. Run `scripts/resolve-latest-model-info`.
|
||||||
|
2. Fetch the returned `migrationGuideUrl` and `promptingGuideUrl` exactly.
|
||||||
|
3. Treat the live guides as canonical.
|
||||||
|
4. If remote retrieval fails, disclose that bundled fallback guidance is being used.
|
||||||
|
|
||||||
|
For an explicit GPT-5.6 Sol or GPT-5.6-family migration:
|
||||||
|
|
||||||
|
1. Preserve the user's explicit target; do not run the latest-model resolver.
|
||||||
|
2. Fetch the live GPT-5.6 model guidance:
|
||||||
|
|
||||||
|
https://developers.openai.com/api/docs/guides/model-guidance?model=gpt-5.6
|
||||||
|
|
||||||
|
3. Read `references/upgrading-to-gpt-5p6-sol.md` for skill-specific migration judgment.
|
||||||
|
4. Read `references/prompting-guide.md` only when prompt changes are needed.
|
||||||
|
|
||||||
|
For another explicit model target, preserve that target and fetch its current official guidance. Do not reuse GPT-5.6-specific defaults, API shapes, or compatibility rules for a different model.
|
||||||
@ -0,0 +1,449 @@
|
|||||||
|
# Upgrading to GPT-5.6 Sol
|
||||||
|
|
||||||
|
Use this guide when the user asks to migrate an existing OpenAI API integration, repository, prompt stack, agent, model router, or model picker to GPT-5.6 Sol or the GPT-5.6 family.
|
||||||
|
|
||||||
|
The default explicit target is `gpt-5.6-sol`. The alias `gpt-5.6` routes to Sol; use it only when the repository intentionally prefers family aliases. Do not treat every old model usage as a Sol candidate: GPT-5.6 is a family with different cost, latency, context, and quality roles.
|
||||||
|
|
||||||
|
Before changing code, use the OpenAI Docs MCP to fetch the current live GPT-5.6 model guidance:
|
||||||
|
|
||||||
|
https://developers.openai.com/api/docs/guides/model-guidance?model=gpt-5.6
|
||||||
|
|
||||||
|
For prompt changes, also read only the `## Prompting Best Practices` section from:
|
||||||
|
|
||||||
|
https://developers.openai.com/api/docs/guides/model-guidance?model=gpt-5.6#prompting-best-practices
|
||||||
|
|
||||||
|
Treat live docs as canonical for current model IDs, parameters, limits, pricing, and feature availability. This file supplies migration judgment: where to look, what can break, what to preserve, what not to adopt automatically, and how to validate the result.
|
||||||
|
|
||||||
|
## Core principle
|
||||||
|
|
||||||
|
Do not perform a blind model-string replacement.
|
||||||
|
|
||||||
|
First preserve the behavior, latency class, cost class, reasoning level, endpoint contract, tool semantics, cache behavior, and output contract of each usage site. Then make the smallest safe migration. Adopt new GPT-5.6 capabilities only when they solve a measured problem or the user explicitly asks for them.
|
||||||
|
|
||||||
|
A model upgrade alone does not authorize adding reasoning fields, changing request schemas, or rewriting tests. Only add explicit reasoning when the old effective behavior is established and omission would change behavior on GPT-5.6.
|
||||||
|
|
||||||
|
The main 5.6 migration hazards are:
|
||||||
|
|
||||||
|
- choosing Sol for workloads that were intentionally mini, nano, low-cost, or latency-sensitive;
|
||||||
|
- inheriting 5.6's default `medium` reasoning where the old effective effort was `none`;
|
||||||
|
- using Chat Completions with function tools without explicitly setting effective reasoning to `none`;
|
||||||
|
- losing prompt-cache hits when a stable prefix is followed by a changing suffix;
|
||||||
|
- increasing image or PDF input tokens because omitted or `auto` detail behaves differently;
|
||||||
|
- applying new cache, persisted-reasoning, Pro, Programmatic Tool Calling, or multi-agent fields to routes that do not support them;
|
||||||
|
- updating model strings but forgetting registries, allowlists, pricing metadata, capability flags, tests, and UI model pickers.
|
||||||
|
|
||||||
|
## Migration posture
|
||||||
|
|
||||||
|
Classify every usage site before editing:
|
||||||
|
|
||||||
|
1. `simple Sol migration`
|
||||||
|
- One flagship model usage.
|
||||||
|
- Same endpoint and request shape can remain.
|
||||||
|
- Reasoning effort is explicit or its old effective value is known.
|
||||||
|
- No cache, vision, file, tool, or parser behavior needs implementation changes.
|
||||||
|
2. `tier-aware family migration`
|
||||||
|
- The repository exposes multiple model roles, model choices, fallbacks, routers, pricing data, or capability metadata.
|
||||||
|
- Map each role to Sol, Terra, or Luna instead of replacing everything with Sol.
|
||||||
|
3. `compatibility migration`
|
||||||
|
- The safe move requires parameter, endpoint, cache, state, tool-loop, or multimodal-detail changes.
|
||||||
|
- Make these changes only when implementation work is inside the user's requested scope. Otherwise report the exact blocker and smallest follow-up.
|
||||||
|
4. `prompt migration`
|
||||||
|
- The API shape can remain, but representative traces show a prompt-specific regression.
|
||||||
|
- Make a surgical prompt edit tied to that failure; do not rewrite a working prompt stack wholesale.
|
||||||
|
- When the task is to update prompting guidance, edit the directly tied prompt surface only. Do not modify runtime request code, model schemas, or tests unless the prompt change requires it.
|
||||||
|
5. `optional feature adoption`
|
||||||
|
- Pro mode, persisted reasoning, explicit caching, Programmatic Tool Calling, or multi-agent behavior is being added deliberately.
|
||||||
|
- Keep this separate from the baseline migration so its effect can be measured.
|
||||||
|
6. `leave unchanged`
|
||||||
|
- Historical examples, documentation about old models, snapshots, fixtures, eval baselines, comparison code, intentionally pinned fallbacks, unsupported providers, or ambiguous usages.
|
||||||
|
|
||||||
|
When intent is unclear, prefer leaving a usage unchanged and list it for confirmation over silently changing its role.
|
||||||
|
|
||||||
|
## Inventory before editing
|
||||||
|
|
||||||
|
Search for more than literal model IDs. Inventory:
|
||||||
|
|
||||||
|
- model strings, aliases, environment variables, CLI flags, config defaults, and deployment settings;
|
||||||
|
- SDK calls to Responses, Chat Completions, Batch, or provider adapters;
|
||||||
|
- reasoning settings, token budgets, sampling settings, and latency timeouts;
|
||||||
|
- function tools, hosted tools, structured outputs, response parsers, and replay logic;
|
||||||
|
- system, developer, user, and tool-description prompts tied to each usage;
|
||||||
|
- routers, fallbacks, model allowlists, enums, regexes, validation schemas, and capability maps;
|
||||||
|
- model picker UI, display labels, descriptions, context limits, pricing metadata, and provider catalogs;
|
||||||
|
- prompt-cache keys, retention options, stable-prefix construction, and cache metrics;
|
||||||
|
- image, PDF, file, OCR, and computer-use inputs;
|
||||||
|
- tests, fixtures, snapshots, evals, analytics labels, billing tables, and docs.
|
||||||
|
|
||||||
|
When changing a default model, search every active default surface: runtime config, environment/config files, setup docs, tests, CLI defaults, and deployment examples. Update them together.
|
||||||
|
|
||||||
|
For each usage site, record:
|
||||||
|
|
||||||
|
- source model and why it appears to be used;
|
||||||
|
- endpoint and SDK/client surface;
|
||||||
|
- prompt surface;
|
||||||
|
- effective reasoning effort, including defaults;
|
||||||
|
- latency, cost, context, and quality role;
|
||||||
|
- tools, structured outputs, caching, state replay, and multimodal inputs;
|
||||||
|
- downstream parsers or user-visible contracts;
|
||||||
|
- migration class and validation plan.
|
||||||
|
|
||||||
|
## Choose the target model by role
|
||||||
|
|
||||||
|
Use this as a starting map, then validate against the repository's workload:
|
||||||
|
|
||||||
|
| Existing role | Starting GPT-5.6 target | Reason |
|
||||||
|
| --- | --- | --- |
|
||||||
|
| Unsuffixed GPT-5 flagship, GPT-5.5, or GPT-5.4 flagship | `gpt-5.6-sol` | Sol is the flagship-equivalent tier. |
|
||||||
|
| Mini model, balanced lower-cost route, or medium-throughput worker | `gpt-5.6-terra` | Terra is the mini-like tier. |
|
||||||
|
| Nano model, classification, extraction, routing, high-volume, or strict-latency route | `gpt-5.6-luna` | Luna is the nano-like tier. |
|
||||||
|
| GPT-4.1 or GPT-4o latency-sensitive flow | Evaluate Luna and Terra first; use Sol only if quality requires it | A flagship replacement can change latency and cost materially. |
|
||||||
|
| Reasoning-heavy or hardest quality-first flow | Start with Sol at the old effective effort | Preserve the reasoning contract before tuning. |
|
||||||
|
| Old Pro usage | Sol plus `reasoning.mode: "pro"`, only if the user wants Pro behavior | GPT-5.6 Pro is a mode, not a separate model slug. |
|
||||||
|
| Router, fallback, or model picker | Add the family by role | Do not collapse a multi-model design into Sol. |
|
||||||
|
| Third-party or provider-specific model | Leave unchanged unless the user explicitly requests provider migration | Model-name similarity is not a safe mapping. |
|
||||||
|
|
||||||
|
Important limits to check in live docs:
|
||||||
|
|
||||||
|
- Sol and Terra have roughly 1.05M context and 128K maximum output.
|
||||||
|
- Luna has a smaller 400K context and 128K maximum output.
|
||||||
|
- Sol and Terra long-context requests above 272K input tokens can change pricing for the full request.
|
||||||
|
|
||||||
|
Do not invent prices, limits, or capability flags. Fetch them from current docs before updating a registry or UI.
|
||||||
|
|
||||||
|
For model pickers and registries, preserve existing model entries by default. Add GPT-5.6 Sol, Terra, and Luna as new options unless the user explicitly asks to replace or remove older models. Do not invent pricing, context limits, capabilities, or metadata unless confirmed from canonical docs.
|
||||||
|
|
||||||
|
If using the `gpt-5.6` alias, record the returned `response.model` during validation. Do not assume an alias and an explicit Sol slug appear identically in dashboards, rate-limit configuration, analytics, or billing metadata.
|
||||||
|
|
||||||
|
## Preserve effective reasoning before tuning
|
||||||
|
|
||||||
|
GPT-5.6 supports `none`, `low`, `medium`, `high`, `xhigh`, and `max`. If omitted, GPT-5.6 defaults to `medium`.
|
||||||
|
|
||||||
|
This is a behavioral migration hazard:
|
||||||
|
|
||||||
|
- GPT-5.5 commonly defaulted to `medium`.
|
||||||
|
- GPT-5.4, mini, and nano usages commonly defaulted to `none`.
|
||||||
|
- A previously omitted setting can therefore become slower, more expensive, and incompatible with Chat Completions function tools after the model swap.
|
||||||
|
|
||||||
|
For each usage:
|
||||||
|
|
||||||
|
1. If effort is explicit, preserve it for the first 5.6 run when supported.
|
||||||
|
2. If effort is omitted and the old effective default is known, add it explicitly only when GPT-5.6's omitted default would change behavior. If both old and new omitted defaults are the same, keep it omitted.
|
||||||
|
3. If the old effective value is unknown, do not guess. Flag it and compare the old behavior with 5.6 at the likely baseline.
|
||||||
|
4. After the baseline passes, test the same setting and one lower on representative tasks.
|
||||||
|
5. Use `xhigh` or `max` only for hard quality-first workloads where evals show a meaningful gain.
|
||||||
|
|
||||||
|
Do not globally recommend `max`. Before increasing effort, check whether the actual failure is a missing success criterion, dependency rule, tool-routing rule, state-replay bug, or validation loop.
|
||||||
|
|
||||||
|
Use the field shape that belongs to the endpoint.
|
||||||
|
|
||||||
|
Responses:
|
||||||
|
|
||||||
|
```json
|
||||||
|
{
|
||||||
|
"model": "gpt-5.6-sol",
|
||||||
|
"reasoning": { "effort": "none" }
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
|
Chat Completions:
|
||||||
|
|
||||||
|
```json
|
||||||
|
{
|
||||||
|
"model": "gpt-5.6-sol",
|
||||||
|
"reasoning_effort": "none"
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
|
## Chat Completions and function tools
|
||||||
|
|
||||||
|
This is the most important endpoint-specific check.
|
||||||
|
|
||||||
|
For GPT-5.6, function tools in Chat Completions are compatible only with effective reasoning `none`. Reasoning with tools should use the Responses API.
|
||||||
|
|
||||||
|
Because GPT-5.6 defaults to `medium`, this combination is unsafe:
|
||||||
|
|
||||||
|
```json
|
||||||
|
{
|
||||||
|
"model": "gpt-5.6-luna",
|
||||||
|
"tools": [{ "type": "function", "function": { "...": "..." } }]
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
|
For a latency-sensitive Chat Completions flow that must keep function tools, explicitly preserve `none`:
|
||||||
|
|
||||||
|
```json
|
||||||
|
{
|
||||||
|
"model": "gpt-5.6-luna",
|
||||||
|
"reasoning_effort": "none",
|
||||||
|
"tools": [{ "type": "function", "function": { "...": "..." } }]
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
|
If the application needs both reasoning and tools:
|
||||||
|
|
||||||
|
- migrate that flow to Responses when implementation changes are in scope;
|
||||||
|
- otherwise report it as a compatibility blocker;
|
||||||
|
- do not hide the incompatibility by removing tools, dropping required reasoning, or changing the workload's behavior without approval.
|
||||||
|
|
||||||
|
If the live API rejects the intended `none` path, treat it as a current API compatibility issue and report the exact request and error rather than inventing a workaround.
|
||||||
|
|
||||||
|
## Responses API and conversation state
|
||||||
|
|
||||||
|
Prefer Responses for reasoning, tools, multi-turn agents, and new 5.6 capabilities.
|
||||||
|
|
||||||
|
For ordinary multi-turn Responses calls, preserve the repository's existing state strategy. Do not add persisted reasoning merely because it exists.
|
||||||
|
|
||||||
|
If deliberately enabling persisted reasoning:
|
||||||
|
|
||||||
|
- use `reasoning.context: "all_turns"` only when the objective and assumptions remain stable;
|
||||||
|
- prefer `previous_response_id` when the server can carry state;
|
||||||
|
- when replaying manually, preserve every prior user input and every relevant output item, not only assistant text;
|
||||||
|
- with `store: false` or ZDR, request and replay `reasoning.encrypted_content`;
|
||||||
|
- use current-turn behavior when old reasoning may be stale or misleading.
|
||||||
|
|
||||||
|
For manual replay, preserve item types, IDs, call IDs, caller metadata, and assistant phase values exactly. Incomplete replay can silently reduce quality or break tool continuation.
|
||||||
|
|
||||||
|
## Prompt caching
|
||||||
|
|
||||||
|
Do not assume old cache-hit behavior survives the model swap.
|
||||||
|
|
||||||
|
GPT-5.6 implicit caching places a managed breakpoint near the latest user or tool message and no longer relies on 128-token rounding. A prompt with a large stable prefix followed by a changing suffix can therefore lose cache hits even when the stable prefix itself has not changed.
|
||||||
|
|
||||||
|
Audit:
|
||||||
|
|
||||||
|
- large reusable system/developer prompts;
|
||||||
|
- dynamic suffixes appended to otherwise stable prompts;
|
||||||
|
- changing timestamps, request IDs, user-specific values, or tool lists in the prefix;
|
||||||
|
- cache keys, retention settings, and cache dashboards;
|
||||||
|
- token accounting that assumes reads only and ignores writes.
|
||||||
|
|
||||||
|
Migration rules:
|
||||||
|
|
||||||
|
- keep reusable prefixes stable;
|
||||||
|
- do not churn large system prompts unnecessarily;
|
||||||
|
- compare old and new `cached_tokens`, `cache_write_tokens`, latency, and cost;
|
||||||
|
- use explicit cache breakpoints only when a measured workload has a stable boundary that implicit caching misses;
|
||||||
|
- do not globally convert every prompt to explicit caching;
|
||||||
|
- do not send 5.6-only cache fields to older routes in a mixed-model system.
|
||||||
|
|
||||||
|
When old and GPT-5.6 routes share a request builder, isolate GPT-5.6-only fields instead of applying them globally.
|
||||||
|
|
||||||
|
The new top-level request shape uses `prompt_cache_options`, for example:
|
||||||
|
|
||||||
|
```json
|
||||||
|
{
|
||||||
|
"prompt_cache_options": {
|
||||||
|
"mode": "explicit",
|
||||||
|
"ttl": "30m"
|
||||||
|
}
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
|
Place explicit breakpoints at the actual stable rendered boundary using `prompt_cache_breakpoint`. Preserve `prompt_cache_key` when the application already uses it. Treat the older `prompt_cache_retention` shape as deprecated and verify the live docs before rewriting it.
|
||||||
|
|
||||||
|
Cache writes cost more than ordinary uncached input, so a lower hit rate can be both slower and more expensive.
|
||||||
|
|
||||||
|
## Images, PDFs, files, and long context
|
||||||
|
|
||||||
|
GPT-5.6 can change token and latency behavior without any prompt change:
|
||||||
|
|
||||||
|
- for image inputs, omitted or `auto` image detail can preserve original dimensions;
|
||||||
|
- for PDF/file inputs in Responses, omitted or `input_file.detail: "auto"` can use high page-image detail;
|
||||||
|
- Chat Completions file inputs do not expose the same detail control;
|
||||||
|
- long-context Sol and Terra requests can cross pricing thresholds;
|
||||||
|
- Luna's smaller context can break workloads that fit in Sol or Terra.
|
||||||
|
|
||||||
|
For multimodal or long-context usages:
|
||||||
|
|
||||||
|
1. Measure input tokens and latency before and after.
|
||||||
|
2. Make detail explicit when cost or latency matters.
|
||||||
|
3. Resize images or use lower detail when the task does not need original spatial precision.
|
||||||
|
4. Keep original/high detail for dense, coordinate-sensitive, OCR, localization, or visual-inspection tasks where it materially improves quality.
|
||||||
|
5. Test worst-case context lengths, not only typical requests.
|
||||||
|
|
||||||
|
Do not claim a capability was removed based only on a missing metadata flag. Verify against current docs and a representative request.
|
||||||
|
|
||||||
|
## Structured outputs, parsers, and tool contracts
|
||||||
|
|
||||||
|
Keep output contracts explicit:
|
||||||
|
|
||||||
|
- preserve JSON schemas, required fields, enums, refusal handling, and parser expectations;
|
||||||
|
- preserve tool names, parameter schemas, call IDs, and retry behavior;
|
||||||
|
- keep citations, evidence fields, or native artifacts when downstream consumers require them;
|
||||||
|
- validate that the final answer still satisfies the contract, not merely that a tool call succeeded.
|
||||||
|
|
||||||
|
Do not fix a failing migration by weakening a schema, deleting required behavior, removing routes, dropping tools, or changing business logic unless the user explicitly asked for that product change.
|
||||||
|
|
||||||
|
## Optional: Pro mode
|
||||||
|
|
||||||
|
Do not enable Pro mode during a baseline migration unless the old usage was Pro-like or the user explicitly asks for it.
|
||||||
|
|
||||||
|
GPT-5.6 Pro uses the base model with a reasoning mode:
|
||||||
|
|
||||||
|
```json
|
||||||
|
{
|
||||||
|
"model": "gpt-5.6-sol",
|
||||||
|
"reasoning": {
|
||||||
|
"mode": "pro",
|
||||||
|
"effort": "medium"
|
||||||
|
}
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
|
Rules:
|
||||||
|
|
||||||
|
- use Responses, not Chat Completions;
|
||||||
|
- do not search for or invent a separate `gpt-5.6-pro` slug;
|
||||||
|
- supported Pro efforts begin at `medium`;
|
||||||
|
- mode and effort are separate decisions;
|
||||||
|
- compare task quality, total latency, and actual billed token usage against standard mode.
|
||||||
|
|
||||||
|
If migrating a legacy Pro slug, make the mode change explicit and evaluate it separately from ordinary Sol migration.
|
||||||
|
|
||||||
|
## Optional: Programmatic Tool Calling
|
||||||
|
|
||||||
|
Programmatic Tool Calling is not a required part of moving to GPT-5.6. Consider it for bounded workflows where code can process several tool results or large intermediate outputs and return a much smaller structured result. Multiple, parallel, or dependent calls alone do not justify it.
|
||||||
|
|
||||||
|
Good candidates:
|
||||||
|
|
||||||
|
- bounded read-only filtering, joining, sorting, ranking, deduplication, and aggregation;
|
||||||
|
- batching many similar records;
|
||||||
|
- repeated deterministic validation;
|
||||||
|
- map-reduce style retrieval with a compact result schema.
|
||||||
|
|
||||||
|
Poor candidates:
|
||||||
|
|
||||||
|
- one direct tool call;
|
||||||
|
- adaptive workflows where each result changes the next decision;
|
||||||
|
- write, approval, or side-effecting flows;
|
||||||
|
- citation-heavy or native-artifact flows;
|
||||||
|
- semantic judgment that should remain visible to the model.
|
||||||
|
|
||||||
|
Request-shape requirements:
|
||||||
|
|
||||||
|
```json
|
||||||
|
{
|
||||||
|
"tools": [
|
||||||
|
{ "type": "programmatic_tool_calling" },
|
||||||
|
{
|
||||||
|
"type": "function",
|
||||||
|
"name": "lookup_records",
|
||||||
|
"allowed_callers": ["programmatic"]
|
||||||
|
}
|
||||||
|
]
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
|
Do not nest `programmatic_tool_calling` under another `tools` property. When enabled, the host must handle `program`, program-issued `function_call`, `function_call_output`, and `program_output` items. Preserve the original `call_id` and `caller` when returning function results.
|
||||||
|
|
||||||
|
Constrain the stage, eligible read-only tools, output schema, retry limit, and handoff back to direct judgment. Test both the `program_output` item and final assistant `message`; a program can return the correct records while the message omits a required field, citation, or caveat.
|
||||||
|
|
||||||
|
## Optional: multi-agent beta
|
||||||
|
|
||||||
|
Do not enable multi-agent behavior during a baseline migration unless the application already has a clear parallelizable workflow and the user asks for it.
|
||||||
|
|
||||||
|
Enabling it requires:
|
||||||
|
|
||||||
|
- the `OpenAI-Beta: responses_multi_agent=v1` header;
|
||||||
|
- `multi_agent: { "enabled": true, "max_concurrent_subagents": 3 }`;
|
||||||
|
- handling `multi_agent_call`, `multi_agent_call_output`, and `agent_message` items;
|
||||||
|
- executing ordinary developer-defined function calls from any agent and returning all required outputs;
|
||||||
|
- preserving new items for replay and tracing;
|
||||||
|
- checking incompatibilities with compaction, reasoning summaries, and tool-call limits in current docs.
|
||||||
|
|
||||||
|
Cap concurrency. Do not let a migration task create unbounded subagents, duplicate work, or finish without a final synthesis.
|
||||||
|
|
||||||
|
## Prompt migration judgment
|
||||||
|
|
||||||
|
After the model and API baseline is working, run representative traces before editing prompts. Change prompts only for measured failures.
|
||||||
|
|
||||||
|
For GPT-5.6, prefer:
|
||||||
|
|
||||||
|
- leaner, outcome-oriented prompts that remove repeated scaffolding while preserving product requirements;
|
||||||
|
- explicit success criteria, dependencies, stopping conditions, and completion boundaries;
|
||||||
|
- preserved user-provided values;
|
||||||
|
- decision criteria for implicit choices instead of universal defaults or keyword maps;
|
||||||
|
- explicit autonomy and permission boundaries;
|
||||||
|
- explicit tool routing, resource links, breadcrumbs, and expected tool choice;
|
||||||
|
- `text.verbosity` for the default level of detail, with prompt instructions for required task-specific content;
|
||||||
|
- staged plans, current-layer awareness, and concise handoffs for long work;
|
||||||
|
- real validation before declaring completion.
|
||||||
|
|
||||||
|
Avoid:
|
||||||
|
|
||||||
|
- untested generic style or process instructions that do not change measured behavior;
|
||||||
|
- blanket language instructions that can cause unwanted language switching;
|
||||||
|
- repeating approval warnings throughout the prompt instead of keeping one clear autonomy policy;
|
||||||
|
- giant prompt rewrites that make the source of a regression impossible to identify;
|
||||||
|
- telling the model to minimize tool loops when correctness, evidence, or required validation needs more work.
|
||||||
|
|
||||||
|
For coding or agentic migrations, add concrete preservation and verification rules:
|
||||||
|
|
||||||
|
```
|
||||||
|
Preserve existing functionality, routes, outputs, and user-visible behavior.
|
||||||
|
Do not delete or disable required behavior merely to make the build pass.
|
||||||
|
Before finishing, run the relevant build, tests, type checks, render or smoke
|
||||||
|
checks, and report the evidence.
|
||||||
|
```
|
||||||
|
|
||||||
|
For long-running work, define the current layer: research, design, implementation, review, or external coordination. Do not let the model silently move to another layer.
|
||||||
|
|
||||||
|
## Upgrade workflow
|
||||||
|
|
||||||
|
1. Fetch current live 5.6 docs and the Prompting Best Practices section.
|
||||||
|
2. Inventory every usage site and its adjacent prompt, config, registry, parser, and test surfaces.
|
||||||
|
3. Classify each usage by role and migration class.
|
||||||
|
4. Choose Sol, Terra, or Luna by the existing workload's role.
|
||||||
|
5. Preserve the old effective reasoning effort explicitly.
|
||||||
|
6. Run the compatibility gates:
|
||||||
|
- endpoint and SDK support;
|
||||||
|
- Chat Completions plus function tools;
|
||||||
|
- cache topology and cache fields;
|
||||||
|
- context length and long-context cost;
|
||||||
|
- image, PDF, and file detail;
|
||||||
|
- structured outputs and parsers;
|
||||||
|
- Responses state replay and tool continuation;
|
||||||
|
- mixed-model routing and unsupported new fields.
|
||||||
|
7. Apply the smallest safe model, config, registry, and prompt changes.
|
||||||
|
8. Do not add optional Pro, persisted reasoning, PTC, explicit caching, or multi-agent behavior unless needed and measurable.
|
||||||
|
9. Run existing tests and representative evals.
|
||||||
|
10. Report changed, unchanged, blocked, and confirmation-needed sites separately.
|
||||||
|
|
||||||
|
## Validation matrix
|
||||||
|
|
||||||
|
Prefer a controlled comparison:
|
||||||
|
|
||||||
|
1. old model + old prompt + old settings;
|
||||||
|
2. GPT-5.6 target + same prompt + preserved effective reasoning;
|
||||||
|
3. GPT-5.6 target + same prompt + one lower effort;
|
||||||
|
4. GPT-5.6 target + the smallest prompt or API fix required by a measured failure;
|
||||||
|
5. optional feature treatment, isolated from the baseline.
|
||||||
|
|
||||||
|
Measure what matters for the workflow:
|
||||||
|
|
||||||
|
- task success and user-visible quality;
|
||||||
|
- structured-output validity and parser success;
|
||||||
|
- tool choice, tool arguments, retries, loop count, and completion rate;
|
||||||
|
- TTFT, end-to-end latency, timeout rate, and concurrency behavior;
|
||||||
|
- input, output, reasoning, cached, and cache-write tokens;
|
||||||
|
- cost per successful task;
|
||||||
|
- long-context, compaction, and replay behavior;
|
||||||
|
- image/PDF token use and visual/OCR accuracy;
|
||||||
|
- completeness, preserved behavior, citations, and validation evidence.
|
||||||
|
|
||||||
|
For model routers and pickers, test at least one representative workload for each role. Verify that the cheapest or fastest tier is not accidentally used for quality-critical work and that Sol is not accidentally used for every workload.
|
||||||
|
|
||||||
|
## Required final report
|
||||||
|
|
||||||
|
Return:
|
||||||
|
|
||||||
|
- `Current usage inventory`: each model site, endpoint, role, prompt surface, and old effective reasoning.
|
||||||
|
- `Target mapping`: Sol, Terra, Luna, unchanged, or confirmation-needed, with the reason.
|
||||||
|
- `Changes made`: model strings, reasoning settings, prompts, registries, metadata, tests, and API-shape changes.
|
||||||
|
- `Compatibility checks`: Chat Completions/tools, caching, state replay, multimodal detail, context/cost, schemas, and mixed-model routing.
|
||||||
|
- `Prompt changes`: each surgical edit and the failure mode it addresses.
|
||||||
|
- `Validation`: commands, evals, traces, before/after measurements, and remaining gaps.
|
||||||
|
- `Unchanged sites`: historical, pinned, ambiguous, or intentionally role-specific usages.
|
||||||
|
- `Blockers and open questions`: exact issue, why it is unsafe to guess, and the smallest next step.
|
||||||
|
|
||||||
|
Never say the migration is complete merely because model strings changed. It is complete only when the affected behavior and contracts have been validated or the remaining gaps are stated explicitly.
|
||||||
598
skills/.system/openai-docs/scripts/fetch-codex-manual.mjs
Normal file
598
skills/.system/openai-docs/scripts/fetch-codex-manual.mjs
Normal file
@ -0,0 +1,598 @@
|
|||||||
|
#!/usr/bin/env node
|
||||||
|
import {
|
||||||
|
access,
|
||||||
|
mkdir,
|
||||||
|
readFile,
|
||||||
|
rename,
|
||||||
|
rm,
|
||||||
|
stat,
|
||||||
|
writeFile,
|
||||||
|
} from "node:fs/promises";
|
||||||
|
import { constants as fsConstants } from "node:fs";
|
||||||
|
import { execFile } from "node:child_process";
|
||||||
|
import { createHash } from "node:crypto";
|
||||||
|
import path from "node:path";
|
||||||
|
import process from "node:process";
|
||||||
|
import { pathToFileURL } from "node:url";
|
||||||
|
import { inspect, promisify } from "node:util";
|
||||||
|
|
||||||
|
const DEFAULT_MANUAL_URL = "https://developers.openai.com/codex/codex-manual.md";
|
||||||
|
const DEFAULT_CACHE_DIR_NAME = "openai-docs-cache";
|
||||||
|
const CACHE_FILE_NAME = "codex-manual.md";
|
||||||
|
const OUTLINE_FILE_NAME = "codex-manual.outline.md";
|
||||||
|
const HASH_HEADER = "x-content-sha256";
|
||||||
|
const USER_AGENT = "codex-openai-docs";
|
||||||
|
const execFileAsync = promisify(execFile);
|
||||||
|
|
||||||
|
class ManualFetchError extends Error {
|
||||||
|
constructor(message, options) {
|
||||||
|
super(message, options);
|
||||||
|
this.name = "ManualFetchError";
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
const sha256 = (value) => createHash("sha256").update(value).digest("hex");
|
||||||
|
|
||||||
|
const withTimeout = async (promiseFactory, timeoutMs) => {
|
||||||
|
const controller = new AbortController();
|
||||||
|
const timeout = setTimeout(() => controller.abort(), timeoutMs);
|
||||||
|
try {
|
||||||
|
return await promiseFactory(controller.signal);
|
||||||
|
} finally {
|
||||||
|
clearTimeout(timeout);
|
||||||
|
}
|
||||||
|
};
|
||||||
|
|
||||||
|
const proxyConfigured = () =>
|
||||||
|
process.env.HTTP_PROXY ||
|
||||||
|
process.env.HTTPS_PROXY ||
|
||||||
|
process.env.http_proxy ||
|
||||||
|
process.env.https_proxy;
|
||||||
|
|
||||||
|
const responseHeaders = (headers) => ({
|
||||||
|
get(name) {
|
||||||
|
return headers.get(name.toLowerCase()) ?? null;
|
||||||
|
},
|
||||||
|
});
|
||||||
|
|
||||||
|
const makeResponse = ({ body, headers, status }) => ({
|
||||||
|
headers: responseHeaders(headers),
|
||||||
|
ok: status >= 200 && status < 300,
|
||||||
|
status,
|
||||||
|
async text() {
|
||||||
|
return body;
|
||||||
|
},
|
||||||
|
});
|
||||||
|
|
||||||
|
const parseCurlHeaders = (rawHeaders) => {
|
||||||
|
const normalized = rawHeaders.replace(/\r\n/g, "\n").trim();
|
||||||
|
const blocks = normalized.split(/\n\n+/).filter(Boolean);
|
||||||
|
const headerBlock = [...blocks]
|
||||||
|
.reverse()
|
||||||
|
.find((block) => block.startsWith("HTTP/"));
|
||||||
|
|
||||||
|
if (!headerBlock) {
|
||||||
|
throw new ManualFetchError("curl did not return HTTP response headers.");
|
||||||
|
}
|
||||||
|
|
||||||
|
const [statusLine, ...lines] = headerBlock.split("\n");
|
||||||
|
const statusMatch = /^HTTP\/\S+\s+(\d{3})/.exec(statusLine);
|
||||||
|
if (!statusMatch) {
|
||||||
|
throw new ManualFetchError(
|
||||||
|
`Could not parse HTTP status from curl response: ${statusLine}`
|
||||||
|
);
|
||||||
|
}
|
||||||
|
|
||||||
|
const headers = new Map();
|
||||||
|
lines.forEach((line) => {
|
||||||
|
const separator = line.indexOf(":");
|
||||||
|
if (separator === -1) return;
|
||||||
|
const name = line.slice(0, separator).trim().toLowerCase();
|
||||||
|
const value = line.slice(separator + 1).trim();
|
||||||
|
headers.set(name, value);
|
||||||
|
});
|
||||||
|
|
||||||
|
return {
|
||||||
|
headers,
|
||||||
|
status: Number(statusMatch[1]),
|
||||||
|
};
|
||||||
|
};
|
||||||
|
|
||||||
|
const tempFilePath = (cacheDir, suffix) =>
|
||||||
|
path.join(
|
||||||
|
cacheDir,
|
||||||
|
`.fetch-codex-manual-${process.pid}-${Date.now()}-${Math.random()
|
||||||
|
.toString(16)
|
||||||
|
.slice(2)}${suffix}`
|
||||||
|
);
|
||||||
|
|
||||||
|
const requestManualWithCurl = async (url, { cacheDir, method, timeoutMs }) => {
|
||||||
|
const headerPath = tempFilePath(cacheDir, ".headers");
|
||||||
|
const bodyPath = tempFilePath(cacheDir, ".body");
|
||||||
|
const curlNames =
|
||||||
|
process.platform === "win32" ? ["curl.exe", "curl"] : ["curl"];
|
||||||
|
const args = [
|
||||||
|
"--silent",
|
||||||
|
"--show-error",
|
||||||
|
"--location",
|
||||||
|
"--dump-header",
|
||||||
|
headerPath,
|
||||||
|
"--output",
|
||||||
|
bodyPath,
|
||||||
|
"--user-agent",
|
||||||
|
USER_AGENT,
|
||||||
|
"--max-time",
|
||||||
|
String(Math.max(1, Math.ceil(timeoutMs / 1000))),
|
||||||
|
];
|
||||||
|
|
||||||
|
if (method === "HEAD") {
|
||||||
|
args.push("--head");
|
||||||
|
} else {
|
||||||
|
args.push("--request", method);
|
||||||
|
}
|
||||||
|
args.push(url);
|
||||||
|
|
||||||
|
let lastError;
|
||||||
|
for (const curlName of curlNames) {
|
||||||
|
try {
|
||||||
|
await execFileAsync(curlName, args, { windowsHide: true });
|
||||||
|
const [rawHeaders, body] = await Promise.all([
|
||||||
|
readFile(headerPath, "utf8"),
|
||||||
|
readFile(bodyPath, "utf8"),
|
||||||
|
]);
|
||||||
|
const { headers, status } = parseCurlHeaders(rawHeaders);
|
||||||
|
return makeResponse({ body, headers, status });
|
||||||
|
} catch (error) {
|
||||||
|
lastError = error;
|
||||||
|
if (error?.code !== "ENOENT") break;
|
||||||
|
} finally {
|
||||||
|
await Promise.all([
|
||||||
|
rm(headerPath, { force: true }),
|
||||||
|
rm(bodyPath, { force: true }),
|
||||||
|
]);
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
if (lastError?.code === "ENOENT") {
|
||||||
|
throw new ManualFetchError("curl is unavailable in this environment.", {
|
||||||
|
cause: lastError,
|
||||||
|
});
|
||||||
|
}
|
||||||
|
throw new ManualFetchError(`${method} ${url} could not be fetched.`, {
|
||||||
|
cause: lastError,
|
||||||
|
});
|
||||||
|
};
|
||||||
|
|
||||||
|
const requestManualWithFetch = async (url, { method, timeoutMs }) => {
|
||||||
|
if (typeof fetch !== "function") {
|
||||||
|
throw new ManualFetchError(
|
||||||
|
"Native fetch is unavailable in this Node runtime."
|
||||||
|
);
|
||||||
|
}
|
||||||
|
|
||||||
|
return withTimeout(
|
||||||
|
(signal) =>
|
||||||
|
fetch(url, {
|
||||||
|
method,
|
||||||
|
headers: { "User-Agent": USER_AGENT },
|
||||||
|
signal,
|
||||||
|
}),
|
||||||
|
timeoutMs
|
||||||
|
);
|
||||||
|
};
|
||||||
|
|
||||||
|
const requestManual = async (url, { cacheDir, method, timeoutMs }) => {
|
||||||
|
const preferCurl = Boolean(proxyConfigured()) || typeof fetch !== "function";
|
||||||
|
const transports = preferCurl
|
||||||
|
? [
|
||||||
|
() => requestManualWithCurl(url, { cacheDir, method, timeoutMs }),
|
||||||
|
() => requestManualWithFetch(url, { method, timeoutMs }),
|
||||||
|
]
|
||||||
|
: [
|
||||||
|
() => requestManualWithFetch(url, { method, timeoutMs }),
|
||||||
|
() => requestManualWithCurl(url, { cacheDir, method, timeoutMs }),
|
||||||
|
];
|
||||||
|
|
||||||
|
let lastError;
|
||||||
|
for (const transport of transports) {
|
||||||
|
try {
|
||||||
|
const response = await transport();
|
||||||
|
if (!response.ok) {
|
||||||
|
throw new ManualFetchError(
|
||||||
|
`${method} ${url} failed with HTTP ${response.status}.`
|
||||||
|
);
|
||||||
|
}
|
||||||
|
return response;
|
||||||
|
} catch (error) {
|
||||||
|
lastError = error;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
throw new ManualFetchError(`${method} ${url} could not be fetched.`, {
|
||||||
|
cause: lastError,
|
||||||
|
});
|
||||||
|
};
|
||||||
|
|
||||||
|
const readHeaderSha = (response) => {
|
||||||
|
const value = response.headers.get(HASH_HEADER);
|
||||||
|
if (!value || !/^[a-f0-9]{64}$/i.test(value)) {
|
||||||
|
throw new ManualFetchError(`Manual response is missing ${HASH_HEADER}.`);
|
||||||
|
}
|
||||||
|
return value.toLowerCase();
|
||||||
|
};
|
||||||
|
|
||||||
|
const nearestExistingParent = async (target) => {
|
||||||
|
let current = target;
|
||||||
|
while (true) {
|
||||||
|
try {
|
||||||
|
const info = await stat(current);
|
||||||
|
return info.isDirectory() ? current : null;
|
||||||
|
} catch (error) {
|
||||||
|
if (error?.code !== "ENOENT") return null;
|
||||||
|
}
|
||||||
|
|
||||||
|
const parent = path.dirname(current);
|
||||||
|
if (parent === current) return null;
|
||||||
|
current = parent;
|
||||||
|
}
|
||||||
|
};
|
||||||
|
|
||||||
|
const usableCacheDir = async (cacheDir) => {
|
||||||
|
if (!cacheDir) return null;
|
||||||
|
const resolved = path.resolve(cacheDir);
|
||||||
|
|
||||||
|
try {
|
||||||
|
const info = await stat(resolved);
|
||||||
|
if (!info.isDirectory()) return null;
|
||||||
|
} catch (error) {
|
||||||
|
if (error?.code !== "ENOENT") return null;
|
||||||
|
}
|
||||||
|
|
||||||
|
const parent = await nearestExistingParent(resolved);
|
||||||
|
if (!parent) return null;
|
||||||
|
|
||||||
|
try {
|
||||||
|
await access(parent, fsConstants.W_OK | fsConstants.X_OK);
|
||||||
|
} catch {
|
||||||
|
return null;
|
||||||
|
}
|
||||||
|
|
||||||
|
return resolved;
|
||||||
|
};
|
||||||
|
|
||||||
|
const defaultCacheDirCandidates = () => {
|
||||||
|
const candidates = [];
|
||||||
|
const seen = new Set();
|
||||||
|
const pushCandidate = (candidate) => {
|
||||||
|
if (!candidate || seen.has(candidate)) return;
|
||||||
|
seen.add(candidate);
|
||||||
|
candidates.push(candidate);
|
||||||
|
};
|
||||||
|
|
||||||
|
[process.env.TMPDIR, process.env.TEMP, process.env.TMP].forEach((baseDir) => {
|
||||||
|
if (baseDir) {
|
||||||
|
pushCandidate(path.join(baseDir, DEFAULT_CACHE_DIR_NAME));
|
||||||
|
}
|
||||||
|
});
|
||||||
|
|
||||||
|
if (process.platform !== "win32") {
|
||||||
|
pushCandidate(`/private/tmp/${DEFAULT_CACHE_DIR_NAME}`);
|
||||||
|
pushCandidate(`/tmp/${DEFAULT_CACHE_DIR_NAME}`);
|
||||||
|
}
|
||||||
|
|
||||||
|
return candidates;
|
||||||
|
};
|
||||||
|
|
||||||
|
const resolveCacheDir = async (cacheDir) => {
|
||||||
|
if (cacheDir) {
|
||||||
|
return usableCacheDir(cacheDir);
|
||||||
|
}
|
||||||
|
|
||||||
|
for (const candidate of defaultCacheDirCandidates()) {
|
||||||
|
const usable = await usableCacheDir(candidate);
|
||||||
|
if (usable) return usable;
|
||||||
|
}
|
||||||
|
|
||||||
|
return null;
|
||||||
|
};
|
||||||
|
|
||||||
|
const cacheFilePath = (cacheDir) => path.join(cacheDir, CACHE_FILE_NAME);
|
||||||
|
|
||||||
|
const outlineFilePath = (cacheDir) => path.join(cacheDir, OUTLINE_FILE_NAME);
|
||||||
|
|
||||||
|
const manualLines = (manual) => {
|
||||||
|
const lines = manual.replace(/\r\n/g, "\n").split("\n");
|
||||||
|
if (lines[lines.length - 1] === "") lines.pop();
|
||||||
|
return lines;
|
||||||
|
};
|
||||||
|
|
||||||
|
const sectionTitle = (rawTitle) =>
|
||||||
|
rawTitle.replace(/\s+#+\s*$/, "").replace(/\s+/g, " ").trim();
|
||||||
|
|
||||||
|
const buildOutline = (manual) => {
|
||||||
|
const lines = manualLines(manual);
|
||||||
|
const headings = [];
|
||||||
|
let inFence = false;
|
||||||
|
|
||||||
|
lines.forEach((line, index) => {
|
||||||
|
if (/^\s*(```|~~~)/.test(line)) {
|
||||||
|
inFence = !inFence;
|
||||||
|
return;
|
||||||
|
}
|
||||||
|
if (inFence) return;
|
||||||
|
|
||||||
|
const match = /^(#{1,6})\s+(.+?)\s*$/.exec(line);
|
||||||
|
if (!match) return;
|
||||||
|
|
||||||
|
const level = match[1].length;
|
||||||
|
if (level < 2 || level > 3) return;
|
||||||
|
|
||||||
|
headings.push({
|
||||||
|
level,
|
||||||
|
title: sectionTitle(match[2]),
|
||||||
|
startLine: index + 1,
|
||||||
|
endLine: lines.length,
|
||||||
|
});
|
||||||
|
});
|
||||||
|
|
||||||
|
for (let index = 0; index < headings.length; index += 1) {
|
||||||
|
const heading = headings[index];
|
||||||
|
const nextPeer = headings
|
||||||
|
.slice(index + 1)
|
||||||
|
.find((candidate) => candidate.level <= heading.level);
|
||||||
|
if (nextPeer) {
|
||||||
|
heading.endLine = nextPeer.startLine - 1;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
if (headings.length === 0) {
|
||||||
|
return {
|
||||||
|
headingCount: 0,
|
||||||
|
lineCount: lines.length,
|
||||||
|
text: "No markdown headings found.",
|
||||||
|
};
|
||||||
|
}
|
||||||
|
|
||||||
|
const minLevel = Math.min(...headings.map((heading) => heading.level));
|
||||||
|
return {
|
||||||
|
headingCount: headings.length,
|
||||||
|
lineCount: lines.length,
|
||||||
|
text: headings
|
||||||
|
.map((heading) => {
|
||||||
|
const indent = " ".repeat(heading.level - minLevel);
|
||||||
|
return `${indent}- ${heading.title} (lines ${heading.startLine}-${heading.endLine})`;
|
||||||
|
})
|
||||||
|
.join("\n"),
|
||||||
|
};
|
||||||
|
};
|
||||||
|
|
||||||
|
const outlineMarkdown = (outline) => `# Codex Manual Outline\n\n${outline.text}\n`;
|
||||||
|
|
||||||
|
const manualStatusLine = (status) =>
|
||||||
|
status.cacheStatus === "hit"
|
||||||
|
? "Manual status: local manual was already current."
|
||||||
|
: "Manual status: local manual was updated.";
|
||||||
|
|
||||||
|
const formatResult = ({ status, outlineText }) =>
|
||||||
|
[
|
||||||
|
`Manual path: ${status.manualPath}`,
|
||||||
|
`Outline path: ${status.outlinePath}`,
|
||||||
|
manualStatusLine(status),
|
||||||
|
"",
|
||||||
|
outlineText,
|
||||||
|
].join("\n");
|
||||||
|
|
||||||
|
const readCachedManual = async (cacheDir, expectedSha256) => {
|
||||||
|
try {
|
||||||
|
const manual = await readFile(cacheFilePath(cacheDir), "utf8");
|
||||||
|
return sha256(manual) === expectedSha256 ? manual : null;
|
||||||
|
} catch {
|
||||||
|
return null;
|
||||||
|
}
|
||||||
|
};
|
||||||
|
|
||||||
|
const writeCachedManual = async (cacheDir, manual) => {
|
||||||
|
await mkdir(cacheDir, { recursive: true });
|
||||||
|
const tmpPath = tempFilePath(cacheDir, `.${CACHE_FILE_NAME}.tmp`);
|
||||||
|
await writeFile(tmpPath, manual, "utf8");
|
||||||
|
await rename(tmpPath, cacheFilePath(cacheDir));
|
||||||
|
};
|
||||||
|
|
||||||
|
const writeOutline = async (cacheDir, outlineText) => {
|
||||||
|
await mkdir(cacheDir, { recursive: true });
|
||||||
|
const tmpPath = tempFilePath(cacheDir, `.${OUTLINE_FILE_NAME}.tmp`);
|
||||||
|
await writeFile(tmpPath, outlineText, "utf8");
|
||||||
|
await rename(tmpPath, outlineFilePath(cacheDir));
|
||||||
|
};
|
||||||
|
|
||||||
|
const fetchCodexManual = async ({
|
||||||
|
manualUrl = DEFAULT_MANUAL_URL,
|
||||||
|
cacheDir,
|
||||||
|
timeoutMs = 30000,
|
||||||
|
} = {}) => {
|
||||||
|
const resolvedCacheDir = await resolveCacheDir(cacheDir);
|
||||||
|
if (!resolvedCacheDir) {
|
||||||
|
throw new ManualFetchError(
|
||||||
|
"Manual cache directory is unavailable; pass --cache-dir to override or use OpenAI Docs MCP fallback."
|
||||||
|
);
|
||||||
|
}
|
||||||
|
await mkdir(resolvedCacheDir, { recursive: true });
|
||||||
|
|
||||||
|
const headResponse = await requestManual(manualUrl, {
|
||||||
|
cacheDir: resolvedCacheDir,
|
||||||
|
method: "HEAD",
|
||||||
|
timeoutMs,
|
||||||
|
});
|
||||||
|
const expectedSha256 = readHeaderSha(headResponse);
|
||||||
|
const manualPath = cacheFilePath(resolvedCacheDir);
|
||||||
|
const outlinePath = outlineFilePath(resolvedCacheDir);
|
||||||
|
const checkedAt = new Date().toISOString();
|
||||||
|
|
||||||
|
const cachedManual = await readCachedManual(resolvedCacheDir, expectedSha256);
|
||||||
|
if (cachedManual !== null) {
|
||||||
|
const outline = buildOutline(cachedManual);
|
||||||
|
const outlineText = outlineMarkdown(outline);
|
||||||
|
await writeOutline(resolvedCacheDir, outlineText);
|
||||||
|
|
||||||
|
return {
|
||||||
|
outlineText,
|
||||||
|
status: {
|
||||||
|
manualUrl,
|
||||||
|
headerSha256: expectedSha256,
|
||||||
|
fetchedManualSha256: expectedSha256,
|
||||||
|
manualHashMatches: true,
|
||||||
|
cacheStatus: "hit",
|
||||||
|
cacheDir: resolvedCacheDir,
|
||||||
|
manualPath,
|
||||||
|
outlinePath,
|
||||||
|
checkedAt,
|
||||||
|
lineCount: outline.lineCount,
|
||||||
|
headingCount: outline.headingCount,
|
||||||
|
},
|
||||||
|
};
|
||||||
|
}
|
||||||
|
|
||||||
|
const getResponse = await requestManual(manualUrl, {
|
||||||
|
cacheDir: resolvedCacheDir,
|
||||||
|
method: "GET",
|
||||||
|
timeoutMs,
|
||||||
|
});
|
||||||
|
const getHeaderSha256 = readHeaderSha(getResponse);
|
||||||
|
if (getHeaderSha256 !== expectedSha256) {
|
||||||
|
throw new ManualFetchError(
|
||||||
|
`${HASH_HEADER} changed between HEAD and GET for ${manualUrl}.`
|
||||||
|
);
|
||||||
|
}
|
||||||
|
|
||||||
|
const manualText = await getResponse.text();
|
||||||
|
const actualSha256 = sha256(manualText);
|
||||||
|
const manualHashMatches = actualSha256 === expectedSha256;
|
||||||
|
if (!manualHashMatches) {
|
||||||
|
throw new ManualFetchError(
|
||||||
|
`${HASH_HEADER} did not match the fetched manual body for ${manualUrl}.`
|
||||||
|
);
|
||||||
|
}
|
||||||
|
|
||||||
|
await writeCachedManual(resolvedCacheDir, manualText);
|
||||||
|
const outline = buildOutline(manualText);
|
||||||
|
const outlineText = outlineMarkdown(outline);
|
||||||
|
await writeOutline(resolvedCacheDir, outlineText);
|
||||||
|
|
||||||
|
return {
|
||||||
|
outlineText,
|
||||||
|
status: {
|
||||||
|
manualUrl,
|
||||||
|
headerSha256: expectedSha256,
|
||||||
|
fetchedManualSha256: actualSha256,
|
||||||
|
manualHashMatches,
|
||||||
|
cacheStatus: "updated",
|
||||||
|
cacheDir: resolvedCacheDir,
|
||||||
|
manualPath,
|
||||||
|
outlinePath,
|
||||||
|
checkedAt,
|
||||||
|
lineCount: outline.lineCount,
|
||||||
|
headingCount: outline.headingCount,
|
||||||
|
},
|
||||||
|
};
|
||||||
|
};
|
||||||
|
|
||||||
|
const parseArgs = (argv) => {
|
||||||
|
const args = {
|
||||||
|
manualUrl: DEFAULT_MANUAL_URL,
|
||||||
|
cacheDir: undefined,
|
||||||
|
timeoutMs: 30000,
|
||||||
|
statusJson: false,
|
||||||
|
};
|
||||||
|
|
||||||
|
for (let index = 0; index < argv.length; index += 1) {
|
||||||
|
const arg = argv[index];
|
||||||
|
if (arg === "--manual-url") {
|
||||||
|
args.manualUrl = argv[++index];
|
||||||
|
} else if (arg === "--cache-dir") {
|
||||||
|
args.cacheDir = argv[++index];
|
||||||
|
} else if (arg === "--timeout-ms") {
|
||||||
|
args.timeoutMs = Number(argv[++index]);
|
||||||
|
} else if (arg === "--status-json") {
|
||||||
|
args.statusJson = true;
|
||||||
|
} else {
|
||||||
|
throw new ManualFetchError(`Unknown argument: ${arg}`);
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
if (!args.manualUrl) {
|
||||||
|
throw new ManualFetchError("--manual-url cannot be empty.");
|
||||||
|
}
|
||||||
|
if (!Number.isFinite(args.timeoutMs) || args.timeoutMs <= 0) {
|
||||||
|
throw new ManualFetchError("--timeout-ms must be a positive number.");
|
||||||
|
}
|
||||||
|
|
||||||
|
return args;
|
||||||
|
};
|
||||||
|
|
||||||
|
const main = async () => {
|
||||||
|
const args = parseArgs(process.argv.slice(2));
|
||||||
|
const { outlineText, status } = await fetchCodexManual(args);
|
||||||
|
|
||||||
|
process.stdout.write(formatResult({ status, outlineText }));
|
||||||
|
|
||||||
|
if (args.statusJson) {
|
||||||
|
console.error(JSON.stringify(status));
|
||||||
|
}
|
||||||
|
};
|
||||||
|
|
||||||
|
const envProxyHint = () => {
|
||||||
|
if (proxyConfigured()) {
|
||||||
|
return "Hint: proxy env vars are present. This helper prefers `curl` in proxied sessions; if requests still fail, verify `curl` is installed and the proxy configuration is valid.";
|
||||||
|
}
|
||||||
|
if (typeof fetch !== "function") {
|
||||||
|
return "Hint: native fetch is unavailable in this Node runtime. Install `curl` or use a newer Node version to fetch the manual.";
|
||||||
|
}
|
||||||
|
if (process.platform === "win32") {
|
||||||
|
return "Hint: on Windows, pass a cache dir under `%TEMP%` or `%TMP%`.";
|
||||||
|
}
|
||||||
|
return null;
|
||||||
|
};
|
||||||
|
|
||||||
|
const formatErrorDetails = (error) => {
|
||||||
|
const details = inspect(error, {
|
||||||
|
breakLength: 120,
|
||||||
|
colors: false,
|
||||||
|
compact: false,
|
||||||
|
depth: 8,
|
||||||
|
});
|
||||||
|
if (!error?.cause) {
|
||||||
|
return details;
|
||||||
|
}
|
||||||
|
|
||||||
|
return `${details}\n\nCause:\n${inspect(error.cause, {
|
||||||
|
breakLength: 120,
|
||||||
|
colors: false,
|
||||||
|
compact: false,
|
||||||
|
depth: 8,
|
||||||
|
})}`;
|
||||||
|
};
|
||||||
|
|
||||||
|
const isCliEntrypoint = () => {
|
||||||
|
const entrypoint = process.argv[1];
|
||||||
|
if (!entrypoint) {
|
||||||
|
return false;
|
||||||
|
}
|
||||||
|
|
||||||
|
return pathToFileURL(entrypoint).href === import.meta.url;
|
||||||
|
};
|
||||||
|
|
||||||
|
if (isCliEntrypoint()) {
|
||||||
|
main().catch((error) => {
|
||||||
|
console.error(`Error: ${error.message}`);
|
||||||
|
const hint = envProxyHint();
|
||||||
|
if (hint) {
|
||||||
|
console.error(hint);
|
||||||
|
}
|
||||||
|
console.error("");
|
||||||
|
console.error("Details:");
|
||||||
|
console.error(formatErrorDetails(error));
|
||||||
|
process.exitCode = 1;
|
||||||
|
});
|
||||||
|
}
|
||||||
|
|
||||||
|
export { DEFAULT_MANUAL_URL, fetchCodexManual };
|
||||||
39
skills/.system/openai-docs/scripts/resolve-latest-model-info
Normal file
39
skills/.system/openai-docs/scripts/resolve-latest-model-info
Normal file
@ -0,0 +1,39 @@
|
|||||||
|
#!/bin/sh
|
||||||
|
set -eu
|
||||||
|
|
||||||
|
SCRIPT_DIR=$(CDPATH= cd -- "$(dirname -- "$0")" && pwd)
|
||||||
|
SCRIPT_PATH="$SCRIPT_DIR/resolve-latest-model-info.cjs"
|
||||||
|
|
||||||
|
is_compatible_node() {
|
||||||
|
"$1" -e 'const major = Number(process.versions.node.split(".")[0]); process.exit(major >= 18 ? 0 : 1)' >/dev/null 2>&1
|
||||||
|
}
|
||||||
|
|
||||||
|
run_if_compatible() {
|
||||||
|
CANDIDATE=$1
|
||||||
|
shift
|
||||||
|
if [ -n "$CANDIDATE" ] && [ -x "$CANDIDATE" ] && is_compatible_node "$CANDIDATE"; then
|
||||||
|
exec "$CANDIDATE" "$SCRIPT_PATH" "$@"
|
||||||
|
fi
|
||||||
|
}
|
||||||
|
|
||||||
|
if [ -n "${NODE:-}" ]; then
|
||||||
|
run_if_compatible "$NODE" "$@"
|
||||||
|
fi
|
||||||
|
|
||||||
|
PATH_NODE=$(command -v node 2>/dev/null || true)
|
||||||
|
if [ -n "$PATH_NODE" ]; then
|
||||||
|
run_if_compatible "$PATH_NODE" "$@"
|
||||||
|
fi
|
||||||
|
|
||||||
|
for CANDIDATE in \
|
||||||
|
"$HOME/.cache/codex-runtimes/codex-primary-runtime/dependencies/node/bin/node" \
|
||||||
|
"$HOME/.cache/codex-runtimes/codex-primary-runtime/dependencies/bin/node" \
|
||||||
|
"/opt/homebrew/bin/node" \
|
||||||
|
"/usr/local/bin/node" \
|
||||||
|
"/usr/bin/node"
|
||||||
|
do
|
||||||
|
run_if_compatible "$CANDIDATE" "$@"
|
||||||
|
done
|
||||||
|
|
||||||
|
echo "No usable Node.js 18+ runtime found for resolve-latest-model-info.cjs" >&2
|
||||||
|
exit 127
|
||||||
165
skills/.system/openai-docs/scripts/resolve-latest-model-info.cjs
Normal file
165
skills/.system/openai-docs/scripts/resolve-latest-model-info.cjs
Normal file
@ -0,0 +1,165 @@
|
|||||||
|
#!/usr/bin/env node
|
||||||
|
|
||||||
|
// Keep this entrypoint CommonJS-safe when the skill is copied into a type=module repo.
|
||||||
|
|
||||||
|
const fs = require("node:fs/promises");
|
||||||
|
const path = require("node:path");
|
||||||
|
|
||||||
|
const DEFAULT_URL =
|
||||||
|
"https://developers.openai.com/api/docs/guides/latest-model.md";
|
||||||
|
const DEFAULT_BASE_URL = "https://developers.openai.com";
|
||||||
|
|
||||||
|
function parseArgs(argv) {
|
||||||
|
const args = {
|
||||||
|
source: process.env.LATEST_MODEL_URL || DEFAULT_URL,
|
||||||
|
baseUrl: process.env.LATEST_MODEL_BASE_URL || DEFAULT_BASE_URL,
|
||||||
|
};
|
||||||
|
|
||||||
|
for (let i = 2; i < argv.length; i += 1) {
|
||||||
|
const arg = argv[i];
|
||||||
|
if (arg === "--source" || arg === "--url") {
|
||||||
|
args.source = argv[i + 1];
|
||||||
|
i += 1;
|
||||||
|
} else if (arg === "--base-url") {
|
||||||
|
args.baseUrl = argv[i + 1];
|
||||||
|
i += 1;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
return args;
|
||||||
|
}
|
||||||
|
|
||||||
|
async function readSource(source) {
|
||||||
|
if (source.startsWith("file://")) {
|
||||||
|
return fs.readFile(new URL(source), "utf8");
|
||||||
|
}
|
||||||
|
|
||||||
|
if (!/^https?:\/\//.test(source)) {
|
||||||
|
return fs.readFile(path.resolve(source), "utf8");
|
||||||
|
}
|
||||||
|
|
||||||
|
let lastError;
|
||||||
|
for (let attempt = 1; attempt <= 3; attempt += 1) {
|
||||||
|
try {
|
||||||
|
const response = await fetch(source, {
|
||||||
|
headers: { accept: "text/markdown,text/plain,*/*" },
|
||||||
|
});
|
||||||
|
|
||||||
|
if (response.ok) {
|
||||||
|
return response.text();
|
||||||
|
}
|
||||||
|
|
||||||
|
lastError = new Error("failed to fetch " + source + ": " + response.status);
|
||||||
|
if (response.status < 500 && response.status !== 429) {
|
||||||
|
break;
|
||||||
|
}
|
||||||
|
} catch (error) {
|
||||||
|
lastError = error;
|
||||||
|
}
|
||||||
|
|
||||||
|
if (attempt < 3) {
|
||||||
|
await new Promise((resolve) => setTimeout(resolve, 250 * attempt));
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
throw lastError;
|
||||||
|
}
|
||||||
|
|
||||||
|
function parseIndentedInfo(lines, startIndex) {
|
||||||
|
const info = {};
|
||||||
|
|
||||||
|
for (let i = startIndex + 1; i < lines.length; i += 1) {
|
||||||
|
const line = lines[i];
|
||||||
|
if (!line.trim()) {
|
||||||
|
continue;
|
||||||
|
}
|
||||||
|
|
||||||
|
const match = line.match(/^ {2}([A-Za-z][A-Za-z0-9_-]*):\s*(.+?)\s*$/);
|
||||||
|
if (!match) {
|
||||||
|
break;
|
||||||
|
}
|
||||||
|
|
||||||
|
info[match[1]] = match[2].replace(/^["']|["']$/g, "");
|
||||||
|
}
|
||||||
|
|
||||||
|
return info;
|
||||||
|
}
|
||||||
|
|
||||||
|
function parseFlatInfo(block) {
|
||||||
|
const info = {};
|
||||||
|
|
||||||
|
for (const line of block.split(/\r?\n/)) {
|
||||||
|
const match = line.match(/^\s*([A-Za-z][A-Za-z0-9_-]*):\s*(.+?)\s*$/);
|
||||||
|
if (match) {
|
||||||
|
info[match[1]] = match[2].replace(/^["']|["']$/g, "");
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
return info;
|
||||||
|
}
|
||||||
|
|
||||||
|
function extractLatestModelInfo(markdown) {
|
||||||
|
const lines = markdown.split(/\r?\n/);
|
||||||
|
const latestModelInfoIndex = lines.findIndex((line) =>
|
||||||
|
/^latestModelInfo:\s*$/.test(line)
|
||||||
|
);
|
||||||
|
|
||||||
|
if (latestModelInfoIndex >= 0) {
|
||||||
|
return parseIndentedInfo(lines, latestModelInfoIndex);
|
||||||
|
}
|
||||||
|
|
||||||
|
const commentMatch = markdown.match(
|
||||||
|
/<!--\s*latestModelInfo\s*\n([\s\S]*?)\n\s*-->/m
|
||||||
|
);
|
||||||
|
if (commentMatch) {
|
||||||
|
return parseFlatInfo(commentMatch[1]);
|
||||||
|
}
|
||||||
|
|
||||||
|
return undefined;
|
||||||
|
}
|
||||||
|
|
||||||
|
function modelToSkillSlug(model) {
|
||||||
|
return model.trim().replace(/\./g, "p");
|
||||||
|
}
|
||||||
|
|
||||||
|
function absoluteUrl(baseUrl, value) {
|
||||||
|
return new URL(value, baseUrl).toString();
|
||||||
|
}
|
||||||
|
|
||||||
|
function normalizeInfo(info, baseUrl) {
|
||||||
|
const model = info?.model?.trim();
|
||||||
|
const migrationGuide = info?.migrationGuide?.trim();
|
||||||
|
const promptingGuide = info?.promptingGuide?.trim();
|
||||||
|
|
||||||
|
if (!model || !migrationGuide || !promptingGuide) {
|
||||||
|
throw new Error(
|
||||||
|
"latestModelInfo must include model, migrationGuide, and promptingGuide"
|
||||||
|
);
|
||||||
|
}
|
||||||
|
|
||||||
|
return {
|
||||||
|
model,
|
||||||
|
modelSlug: modelToSkillSlug(model),
|
||||||
|
migrationGuideUrl: absoluteUrl(baseUrl, migrationGuide),
|
||||||
|
promptingGuideUrl: absoluteUrl(baseUrl, promptingGuide),
|
||||||
|
};
|
||||||
|
}
|
||||||
|
|
||||||
|
async function main() {
|
||||||
|
const { source, baseUrl } = parseArgs(process.argv);
|
||||||
|
const markdown = await readSource(source);
|
||||||
|
const info = extractLatestModelInfo(markdown);
|
||||||
|
|
||||||
|
if (!info) {
|
||||||
|
throw new Error(`latestModelInfo block not found in ${source}`);
|
||||||
|
}
|
||||||
|
|
||||||
|
process.stdout.write(
|
||||||
|
`${JSON.stringify(normalizeInfo(info, baseUrl), null, 2)}\n`
|
||||||
|
);
|
||||||
|
}
|
||||||
|
|
||||||
|
main().catch((error) => {
|
||||||
|
console.error(error.message);
|
||||||
|
process.exit(1);
|
||||||
|
});
|
||||||
243
skills/.system/plugin-creator/SKILL.md
Normal file
243
skills/.system/plugin-creator/SKILL.md
Normal file
@ -0,0 +1,243 @@
|
|||||||
|
---
|
||||||
|
name: plugin-creator
|
||||||
|
description: Create and scaffold plugin directories for Codex with a required `.codex-plugin/plugin.json`, optional plugin folders/files, valid manifest defaults, and personal-marketplace entries by default. Use when Codex needs to create a new personal plugin, add optional plugin structure, generate or update marketplace entries for plugin ordering and availability metadata, or update an existing local plugin during development with the CLI-driven cachebuster and reinstall flow.
|
||||||
|
---
|
||||||
|
|
||||||
|
# Plugin Creator
|
||||||
|
|
||||||
|
## Quick Start
|
||||||
|
|
||||||
|
1. Run the scaffold script:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
# Plugin names are normalized to lower-case hyphen-case and must be <= 64 chars.
|
||||||
|
# The generated folder and plugin.json name are always the same.
|
||||||
|
# Run from the skill root (the directory containing this `SKILL.md`).
|
||||||
|
# By default creates in `~/plugins/<plugin-name>`.
|
||||||
|
python3 scripts/create_basic_plugin.py <plugin-name>
|
||||||
|
```
|
||||||
|
|
||||||
|
2. Edit `<plugin-path>/.codex-plugin/plugin.json` when the request gives specific metadata.
|
||||||
|
The scaffold starts with valid defaults and must not contain `[TODO: ...]` placeholders.
|
||||||
|
|
||||||
|
3. Generate or update the personal marketplace entry when the plugin should appear in Codex UI ordering:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
# Personal marketplace entries default to `~/.agents/plugins/marketplace.json`.
|
||||||
|
python3 scripts/create_basic_plugin.py my-plugin --with-marketplace
|
||||||
|
```
|
||||||
|
|
||||||
|
Only specify `--marketplace-name <name>` when the default `personal` marketplace name is already
|
||||||
|
taken or installed and you need to seed a different new marketplace file:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
python3 scripts/create_basic_plugin.py my-plugin \
|
||||||
|
--with-marketplace \
|
||||||
|
--marketplace-name team-local
|
||||||
|
```
|
||||||
|
|
||||||
|
Only use a repo/team marketplace when the user specifically asks for that destination:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
python3 scripts/create_basic_plugin.py my-plugin \
|
||||||
|
--path <repo-root>/plugins \
|
||||||
|
--marketplace-path <repo-root>/.agents/plugins/marketplace.json \
|
||||||
|
--with-marketplace
|
||||||
|
```
|
||||||
|
|
||||||
|
When the user specifies a marketplace path, make sure that marketplace is actually installed before
|
||||||
|
telling the user to reinstall from it. The default personal marketplace file at
|
||||||
|
`~/.agents/plugins/marketplace.json` is discovered implicitly, but other marketplace paths are not.
|
||||||
|
On Windows, use the equivalent path under the user profile.
|
||||||
|
|
||||||
|
4. Generate/adjust optional companion folders as needed:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
python3 scripts/create_basic_plugin.py my-plugin \
|
||||||
|
--path <parent-plugin-directory> \
|
||||||
|
--marketplace-path <marketplace-json-path> \
|
||||||
|
--with-skills --with-hooks --with-scripts --with-assets --with-mcp --with-apps --with-marketplace
|
||||||
|
```
|
||||||
|
|
||||||
|
`<parent-plugin-directory>` is the directory where the plugin folder `<plugin-name>` will be
|
||||||
|
created (for example `~/plugins`).
|
||||||
|
|
||||||
|
5. Before handing back a generated plugin, run:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
python3 scripts/validate_plugin.py <plugin-path>
|
||||||
|
```
|
||||||
|
|
||||||
|
For updates to an existing local plugin during development, keep the scaffold flow as-is and use the
|
||||||
|
reference instead of hand-editing marketplace files:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
python3 scripts/update_plugin_cachebuster.py <plugin-path>
|
||||||
|
```
|
||||||
|
|
||||||
|
Prefer the helper default cachebuster unless the user explicitly asks for a specific override.
|
||||||
|
See `references/installing-and-updating.md` for the expected cachebuster and reinstall flow while iterating on an existing local plugin.
|
||||||
|
|
||||||
|
## What this skill creates
|
||||||
|
|
||||||
|
- Default marketplace-backed scaffolds use the personal marketplace file at
|
||||||
|
`~/.agents/plugins/marketplace.json`, with plugins generally being stored in
|
||||||
|
`~/plugins/<plugin-name>/`.
|
||||||
|
- Creates plugin root at `/<parent-plugin-directory>/<plugin-name>/`.
|
||||||
|
- Always creates `/<parent-plugin-directory>/<plugin-name>/.codex-plugin/plugin.json`.
|
||||||
|
- Fills the manifest with the validated schema shape that the ingestion path accepts.
|
||||||
|
- Creates or updates `~/.agents/plugins/marketplace.json` when `--with-marketplace` is set.
|
||||||
|
- If the marketplace file does not exist yet, seed a personal marketplace root before adding the first plugin entry.
|
||||||
|
- `<plugin-name>` is normalized using skill-creator naming rules:
|
||||||
|
- `My Plugin` → `my-plugin`
|
||||||
|
- `My--Plugin` → `my-plugin`
|
||||||
|
- underscores, spaces, and punctuation are converted to `-`
|
||||||
|
- result is lower-case hyphen-delimited with consecutive hyphens collapsed
|
||||||
|
- Supports optional creation of:
|
||||||
|
- `skills/`
|
||||||
|
- `hooks/`
|
||||||
|
- `scripts/`
|
||||||
|
- `assets/`
|
||||||
|
- `.mcp.json`
|
||||||
|
- `.app.json`
|
||||||
|
|
||||||
|
## Marketplace workflow
|
||||||
|
|
||||||
|
- Personal-marketplace creation defaults to `~/.agents/plugins/marketplace.json`. Here,
|
||||||
|
"personal marketplace" means the marketplace whose file is at that path.
|
||||||
|
- Repo/team marketplace creation is opt-in through both `--path` and `--marketplace-path`, only
|
||||||
|
when the user specifically requests it.
|
||||||
|
- `--marketplace-name` is an exception path. Use it only when the default `personal` marketplace
|
||||||
|
name is already taken and you need to seed a different new marketplace file.
|
||||||
|
- Do not use `--marketplace-name` to rename an existing marketplace file in place. If the file
|
||||||
|
already exists, its top-level `name` must already match.
|
||||||
|
- If the user specifies a different marketplace path, treat that marketplace as needing explicit installation via `codex plugin marketplace add`.
|
||||||
|
- Prefer `scripts/read_marketplace_name.py` when you need the marketplace name from any
|
||||||
|
`marketplace.json` file. With no argument it reads the default personal marketplace; with an
|
||||||
|
explicit path it works for repo/team marketplaces too.
|
||||||
|
- In either location, the generated source path remains `./plugins/<plugin-name>`.
|
||||||
|
- Marketplace root metadata supports top-level `name` plus optional `interface.displayName`.
|
||||||
|
- Treat plugin order in `plugins[]` as render order in Codex. Append new entries unless a user explicitly asks to reorder the list.
|
||||||
|
- `displayName` belongs inside the marketplace `interface` object, not individual `plugins[]` entries.
|
||||||
|
- Each generated marketplace entry must include all of:
|
||||||
|
- `policy.installation`
|
||||||
|
- `policy.authentication`
|
||||||
|
- `category`
|
||||||
|
- Default new entries to:
|
||||||
|
- `policy.installation: "AVAILABLE"`
|
||||||
|
- `policy.authentication: "ON_INSTALL"`
|
||||||
|
- Override defaults only when the user explicitly specifies another allowed value.
|
||||||
|
- Allowed `policy.installation` values:
|
||||||
|
- `NOT_AVAILABLE`
|
||||||
|
- `AVAILABLE`
|
||||||
|
- `INSTALLED_BY_DEFAULT`
|
||||||
|
- Allowed `policy.authentication` values:
|
||||||
|
- `ON_INSTALL`
|
||||||
|
- `ON_USE`
|
||||||
|
- Treat `policy.products` as an override. Omit it unless the user explicitly requests product gating.
|
||||||
|
- The generated plugin entry shape is:
|
||||||
|
|
||||||
|
```json
|
||||||
|
{
|
||||||
|
"name": "plugin-name",
|
||||||
|
"source": {
|
||||||
|
"source": "local",
|
||||||
|
"path": "./plugins/plugin-name"
|
||||||
|
},
|
||||||
|
"policy": {
|
||||||
|
"installation": "AVAILABLE",
|
||||||
|
"authentication": "ON_INSTALL"
|
||||||
|
},
|
||||||
|
"category": "Productivity"
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
|
- Use `--force` only when intentionally replacing an existing marketplace entry for the same plugin name.
|
||||||
|
- If the target marketplace file does not exist yet, create it with top-level `"name"`, an `"interface"` object containing `"displayName"`, and a `plugins` array, then add the new entry.
|
||||||
|
|
||||||
|
- For a brand-new marketplace file, the root object should look like:
|
||||||
|
|
||||||
|
```json
|
||||||
|
{
|
||||||
|
"name": "personal",
|
||||||
|
"interface": {
|
||||||
|
"displayName": "Personal"
|
||||||
|
},
|
||||||
|
"plugins": [
|
||||||
|
{
|
||||||
|
"name": "plugin-name",
|
||||||
|
"source": {
|
||||||
|
"source": "local",
|
||||||
|
"path": "./plugins/plugin-name"
|
||||||
|
},
|
||||||
|
"policy": {
|
||||||
|
"installation": "AVAILABLE",
|
||||||
|
"authentication": "ON_INSTALL"
|
||||||
|
},
|
||||||
|
"category": "Productivity"
|
||||||
|
}
|
||||||
|
]
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
|
## Required behavior
|
||||||
|
|
||||||
|
- Outer folder name and `plugin.json` `"name"` are always the same normalized plugin name.
|
||||||
|
- Do not remove required structure; keep `.codex-plugin/plugin.json` present.
|
||||||
|
- Do not leave `[TODO: ...]` placeholders in plugin manifests.
|
||||||
|
- Keep `apps` and `mcpServers` out of `plugin.json` unless their companion files are actually created.
|
||||||
|
- Omit unsupported plugin manifest fields that validation rejects, including `hooks`.
|
||||||
|
- If creating files inside an existing plugin path, use `--force` only when overwrite is intentional.
|
||||||
|
- Preserve any existing marketplace `interface.displayName`.
|
||||||
|
- When generating marketplace entries, always write `policy.installation`, `policy.authentication`, and `category` even if their values are defaults.
|
||||||
|
- Add `policy.products` only when the user explicitly asks for that override.
|
||||||
|
- Keep marketplace `source.path` relative to the selected marketplace root as `./plugins/<plugin-name>`.
|
||||||
|
- Only use `--marketplace-name` when creating a new marketplace file whose name should not be
|
||||||
|
`personal` because that name is already taken or installed elsewhere.
|
||||||
|
- If Codex would need approval to write the marketplace file, ask for that approval before
|
||||||
|
proceeding. If the user prefers to run the write themselves, provide the exact scaffold command
|
||||||
|
and then continue from validation or subsequent plugin edits instead of leaving the workflow
|
||||||
|
vague.
|
||||||
|
- For updates to an existing local plugin during development, do not hand-edit marketplace config
|
||||||
|
or `marketplace.json`. Use the update flow documented in
|
||||||
|
`references/installing-and-updating.md` and `scripts/update_plugin_cachebuster.py`.
|
||||||
|
- Do not tell the user to run `codex plugin marketplace add` for the default personal-marketplace
|
||||||
|
flow. That command is for explicit non-default marketplace configuration, not for the standard
|
||||||
|
`~/.agents/plugins/marketplace.json` path.
|
||||||
|
- If the user provided a non-default `--marketplace-path`, make sure that marketplace is installed
|
||||||
|
before giving reinstall instructions. Use `codex plugin marketplace add <path-to-marketplace-root>`
|
||||||
|
when that explicit marketplace has not been configured yet.
|
||||||
|
- When the workflow created or updated a marketplace-backed plugin, end the final user-facing
|
||||||
|
response with a short Codex app handoff. Say `To view this in the Codex app:` and write
|
||||||
|
`View <normalized plugin name>` and `Share <normalized plugin name>` as Markdown links, not raw
|
||||||
|
URLs or code spans.
|
||||||
|
- The View deeplink uses `codex://plugins/<normalized plugin name>?marketplacePath=<absolute marketplace.json path>`.
|
||||||
|
The Share deeplink uses the same URL with `&mode=share`.
|
||||||
|
- Replace the placeholders with the real normalized plugin name and absolute `marketplace.json`
|
||||||
|
path from the scaffolded plugin. URL-encode the path segment and query value when needed.
|
||||||
|
- Do not add `pluginName` or `hostId` query parameters to these deeplinks. Codex derives both after
|
||||||
|
the user clicks the link.
|
||||||
|
- Do not emit the `View <normalized plugin name>` or `Share <normalized plugin name>` links when no marketplace entry was
|
||||||
|
created or updated.
|
||||||
|
|
||||||
|
## Reference to exact spec sample
|
||||||
|
|
||||||
|
For the exact canonical sample JSON for both plugin manifests and marketplace entries, use:
|
||||||
|
|
||||||
|
- `references/plugin-json-spec.md`
|
||||||
|
- `references/installing-and-updating.md` for update/reinstall guidance while
|
||||||
|
iterating on an existing local plugin, plus the new-thread pickup behavior after reinstall
|
||||||
|
|
||||||
|
## Validation
|
||||||
|
|
||||||
|
After editing `SKILL.md`, run:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
python3 ../skill-creator/scripts/quick_validate.py .
|
||||||
|
```
|
||||||
|
|
||||||
|
Before handing back a generated plugin, run:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
python3 scripts/validate_plugin.py <plugin-path>
|
||||||
|
```
|
||||||
6
skills/.system/plugin-creator/agents/openai.yaml
Normal file
6
skills/.system/plugin-creator/agents/openai.yaml
Normal file
@ -0,0 +1,6 @@
|
|||||||
|
interface:
|
||||||
|
display_name: "Plugin Creator"
|
||||||
|
short_description: "Scaffold plugins and marketplace entries"
|
||||||
|
default_prompt: "Use $plugin-creator to scaffold a valid plugin in the personal marketplace, then validate it before handing it back."
|
||||||
|
icon_small: "./assets/plugin-creator-small.svg"
|
||||||
|
icon_large: "./assets/plugin-creator.png"
|
||||||
@ -0,0 +1,3 @@
|
|||||||
|
<svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" fill="currentColor" viewBox="0 0 20 20">
|
||||||
|
<path fill="#0D0D0D" d="M12.03 4.113a3.612 3.612 0 0 1 5.108 5.108l-6.292 6.29c-.324.324-.56.561-.791.752l-.235.176c-.205.14-.422.261-.65.36l-.229.093a4.136 4.136 0 0 1-.586.16l-.764.134-2.394.4c-.142.024-.294.05-.423.06-.098.007-.232.01-.378-.026l-.149-.05a1.081 1.081 0 0 1-.521-.474l-.046-.093a1.104 1.104 0 0 1-.075-.527c.01-.129.035-.28.06-.422l.398-2.394c.1-.602.162-.987.295-1.35l.093-.23c.1-.228.22-.445.36-.65l.176-.235c.19-.232.428-.467.751-.79l6.292-6.292Zm-5.35 7.232c-.35.35-.534.535-.66.688l-.11.147a2.67 2.67 0 0 0-.24.433l-.062.154c-.08.22-.124.462-.232 1.112l-.398 2.394-.001.001h.003l2.393-.399.717-.126a2.63 2.63 0 0 0 .394-.105l.154-.063a2.65 2.65 0 0 0 .433-.24l.147-.11c.153-.126.339-.31.688-.66l4.988-4.988-3.227-3.226-4.987 4.988Zm9.517-6.291a2.281 2.281 0 0 0-3.225 0l-.364.362 3.226 3.227.363-.364c.89-.89.89-2.334 0-3.225ZM4.583 1.783a.3.3 0 0 1 .294.241c.117.585.347 1.092.707 1.48.357.385.859.668 1.549.783a.3.3 0 0 1 0 .592c-.69.115-1.192.398-1.549.783-.315.34-.53.77-.657 1.265l-.05.215a.3.3 0 0 1-.588 0c-.117-.585-.347-1.092-.707-1.48-.357-.384-.859-.668-1.549-.783a.3.3 0 0 1 0-.592c.69-.115 1.192-.398 1.549-.783.36-.388.59-.895.707-1.48l.015-.05a.3.3 0 0 1 .279-.19Z"/>
|
||||||
|
</svg>
|
||||||
|
After Width: | Height: | Size: 1.3 KiB |
BIN
skills/.system/plugin-creator/assets/plugin-creator.png
Normal file
BIN
skills/.system/plugin-creator/assets/plugin-creator.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 1.5 KiB |
@ -0,0 +1,143 @@
|
|||||||
|
# Updating Existing Local Plugins
|
||||||
|
|
||||||
|
Use this reference when a plugin already exists and the request is about updating the plugin during
|
||||||
|
local development.
|
||||||
|
|
||||||
|
All scripts here are specified relative to the skill root. Update the path for running the scripts
|
||||||
|
depending on your current working directory.
|
||||||
|
|
||||||
|
## When To Use This Flow
|
||||||
|
|
||||||
|
Use this flow when all of the following are true:
|
||||||
|
|
||||||
|
- the plugin already exists locally
|
||||||
|
- the marketplace entry already points at the plugin source you are editing
|
||||||
|
- the user wants Codex to see the updated plugin without manually editing marketplace files
|
||||||
|
|
||||||
|
If the user still needs the initial plugin entry or marketplace structure created, use the scaffold
|
||||||
|
flow first and only then switch to this reinstall flow.
|
||||||
|
|
||||||
|
## Update Loop
|
||||||
|
|
||||||
|
1. Update the plugin manifest to a single Codex cachebuster suffix:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
python3 scripts/update_plugin_cachebuster.py \
|
||||||
|
<plugin-path>
|
||||||
|
```
|
||||||
|
|
||||||
|
Prefer the default helper behavior here. If you omit `--cachebuster`, the helper uses a UTC
|
||||||
|
timestamp down to seconds, which is the recommended path for routine local iteration.
|
||||||
|
|
||||||
|
Only use a manual cachebuster override when the user explicitly asks for one or when a workflow
|
||||||
|
outside Codex depends on a specific token:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
python3 scripts/update_plugin_cachebuster.py \
|
||||||
|
<plugin-path> \
|
||||||
|
--cachebuster local-20260519-184516
|
||||||
|
```
|
||||||
|
|
||||||
|
2. For the default scaffolded flow, read the marketplace name from the personal marketplace file:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
python3 scripts/read_marketplace_name.py
|
||||||
|
```
|
||||||
|
|
||||||
|
Here, "personal marketplace" means the marketplace whose file is at
|
||||||
|
`~/.agents/plugins/marketplace.json`. On Windows, use the equivalent path under the user profile.
|
||||||
|
The helper uses Python's home-directory resolution and prints the marketplace name to use when
|
||||||
|
constructing the install command.
|
||||||
|
|
||||||
|
To read the name from a different marketplace file, pass the path directly:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
python3 scripts/read_marketplace_name.py --marketplace-path <path-to-marketplace.json>
|
||||||
|
```
|
||||||
|
|
||||||
|
3. Reinstall from that marketplace name:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
codex plugin add <plugin-name>@<marketplace-name-from-marketplace-json>
|
||||||
|
```
|
||||||
|
|
||||||
|
The default personal marketplace is discovered implicitly from
|
||||||
|
`~/.agents/plugins/marketplace.json`. You do not need `codex plugin marketplace add` for that
|
||||||
|
path, and `codex plugin marketplace list` is not the right check for whether that default
|
||||||
|
marketplace exists.
|
||||||
|
|
||||||
|
4. If the plugin is not using the personal marketplace file, check which configured local
|
||||||
|
marketplace is actually surfacing that plugin:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
codex plugin list
|
||||||
|
```
|
||||||
|
|
||||||
|
If the plugin is not in the personal marketplace file, confirm which marketplace entry points at
|
||||||
|
the plugin source you are editing and make sure that marketplace is still local. If it is a
|
||||||
|
different local marketplace, reinstall from that marketplace name instead of forcing the personal
|
||||||
|
marketplace flow. If it is not local, stop and help the user resolve the mismatch before
|
||||||
|
continuing.
|
||||||
|
|
||||||
|
5. If the plugin lives in a different confirmed local marketplace, substitute that marketplace
|
||||||
|
name:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
codex plugin add <plugin-name>@<local-marketplace>
|
||||||
|
```
|
||||||
|
|
||||||
|
6. Prompt the user to use a new thread to try the updated plugin, so that Codex picks up new skills
|
||||||
|
and tools.
|
||||||
|
|
||||||
|
## Cachebuster Policy
|
||||||
|
|
||||||
|
- Preserve the existing version prefix and replace only the suffix.
|
||||||
|
- Treat the preserved prefix as everything before `+`.
|
||||||
|
- Use the format:
|
||||||
|
|
||||||
|
```text
|
||||||
|
<base-version>+codex.<cachebuster>
|
||||||
|
```
|
||||||
|
|
||||||
|
Examples:
|
||||||
|
|
||||||
|
- `0.1.0` → `0.1.0+codex.local-20260519-184516`
|
||||||
|
- `0.1.0+codex.old-token` → `0.1.0+codex.local-20260519-184516`
|
||||||
|
- `1.2.3-beta.1+codex.prev` → `1.2.3-beta.1+codex.local-20260519-184516`
|
||||||
|
- `dev-build+other-tag` → `dev-build+codex.local-20260519-184516`
|
||||||
|
|
||||||
|
Replace the existing Codex cachebuster instead of appending another one. Do not keep incrementing
|
||||||
|
numeric version components just to trigger reinstall behavior.
|
||||||
|
|
||||||
|
## Marketplace Rules
|
||||||
|
|
||||||
|
- Marketplace manipulation should happen through commands, not by hand-editing `marketplace.json`
|
||||||
|
or `config.toml` during this update/reinstall flow.
|
||||||
|
- Prefer the personal marketplace file for the default scaffolded flow.
|
||||||
|
- Read the personal marketplace name with
|
||||||
|
`python3 scripts/read_marketplace_name.py` and use the printed value when constructing
|
||||||
|
`codex plugin add <plugin-name>@<marketplace-name>`.
|
||||||
|
- For non-default marketplace files, use
|
||||||
|
`python3 scripts/read_marketplace_name.py --marketplace-path <path-to-marketplace.json>` to read
|
||||||
|
the name before constructing reinstall commands.
|
||||||
|
- Do not tell the user to run `codex plugin marketplace add` for the default personal-marketplace
|
||||||
|
flow. That marketplace is discovered implicitly by Codex.
|
||||||
|
- If the user specified a different marketplace path, make sure that marketplace is installed
|
||||||
|
before giving install or reinstall instructions. Non-default marketplace paths are not
|
||||||
|
discovered implicitly.
|
||||||
|
- Use `codex plugin list` when the plugin lives in a different configured marketplace and you need
|
||||||
|
to confirm which marketplace is surfacing that plugin.
|
||||||
|
- If a non-default local marketplace has not been configured yet, install it with
|
||||||
|
`codex plugin marketplace add <path-to-marketplace-root>` before telling the user to run
|
||||||
|
`codex plugin add <plugin-name>@<marketplace-name>`.
|
||||||
|
- If the plugin is not in the personal marketplace file, confirm that the selected marketplace is
|
||||||
|
local before telling the user to reinstall from it.
|
||||||
|
- If the selected marketplace is not local, stop and help the user resolve that mismatch rather
|
||||||
|
than pretending the normal local reinstall flow applies.
|
||||||
|
- If the plugin source is not already the source referenced by the chosen marketplace entry, stop
|
||||||
|
and fix that first. This update flow does not rewrite marketplace entries.
|
||||||
|
|
||||||
|
## After Reinstall
|
||||||
|
|
||||||
|
After reinstalling, prompt the user to start a new thread for testing. That is the safe boundary for
|
||||||
|
picking up the updated plugin and its MCP tools.
|
||||||
218
skills/.system/plugin-creator/references/plugin-json-spec.md
Normal file
218
skills/.system/plugin-creator/references/plugin-json-spec.md
Normal file
@ -0,0 +1,218 @@
|
|||||||
|
# Plugin JSON sample spec
|
||||||
|
|
||||||
|
```json
|
||||||
|
{
|
||||||
|
"name": "plugin-name",
|
||||||
|
"version": "1.2.0",
|
||||||
|
"description": "Brief plugin description",
|
||||||
|
"author": {
|
||||||
|
"name": "Author Name",
|
||||||
|
"email": "author@example.com",
|
||||||
|
"url": "https://github.com/author"
|
||||||
|
},
|
||||||
|
"homepage": "https://docs.example.com/plugin",
|
||||||
|
"repository": "https://github.com/author/plugin",
|
||||||
|
"license": "MIT",
|
||||||
|
"keywords": ["keyword1", "keyword2"],
|
||||||
|
"skills": "./skills/",
|
||||||
|
"hooks": "./hooks.json",
|
||||||
|
"mcpServers": "./.mcp.json",
|
||||||
|
"apps": "./.app.json",
|
||||||
|
"interface": {
|
||||||
|
"displayName": "Plugin Display Name",
|
||||||
|
"shortDescription": "Short description for subtitle",
|
||||||
|
"longDescription": "Long description for details page",
|
||||||
|
"developerName": "OpenAI",
|
||||||
|
"category": "Productivity",
|
||||||
|
"capabilities": ["Interactive", "Write"],
|
||||||
|
"websiteURL": "https://openai.com/",
|
||||||
|
"privacyPolicyURL": "https://openai.com/policies/row-privacy-policy/",
|
||||||
|
"termsOfServiceURL": "https://openai.com/policies/row-terms-of-use/",
|
||||||
|
"defaultPrompt": [
|
||||||
|
"Summarize my inbox and draft replies for me.",
|
||||||
|
"Find open bugs and turn them into Linear tickets.",
|
||||||
|
"Review today's meetings and flag scheduling gaps."
|
||||||
|
],
|
||||||
|
"brandColor": "#3B82F6",
|
||||||
|
"composerIcon": "./assets/icon.png",
|
||||||
|
"logo": "./assets/logo.png",
|
||||||
|
"logoDark": "./assets/logo-dark.png",
|
||||||
|
"screenshots": [
|
||||||
|
"./assets/screenshot1.png",
|
||||||
|
"./assets/screenshot2.png",
|
||||||
|
"./assets/screenshot3.png"
|
||||||
|
]
|
||||||
|
}
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
|
## Field guide
|
||||||
|
|
||||||
|
### Top-level fields
|
||||||
|
|
||||||
|
- `name` (`string`): Plugin identifier (kebab-case, no spaces). Required if `plugin.json` is provided and used as manifest name and component namespace.
|
||||||
|
- `version` (`string`): Plugin semantic version.
|
||||||
|
- `description` (`string`): Short purpose summary.
|
||||||
|
- `author` (`object`): Publisher identity.
|
||||||
|
- `name` (`string`): Author or team name.
|
||||||
|
- `email` (`string`): Contact email.
|
||||||
|
- `url` (`string`): Author/team homepage or profile URL.
|
||||||
|
- `homepage` (`string`): Documentation URL for plugin usage.
|
||||||
|
- `repository` (`string`): Source code URL.
|
||||||
|
- `license` (`string`): License identifier (for example `MIT`, `Apache-2.0`).
|
||||||
|
- `keywords` (`array` of `string`): Search/discovery tags.
|
||||||
|
- `skills` (`string`): Relative path to skill directories/files.
|
||||||
|
- `hooks` (`string`): Hook config path.
|
||||||
|
- `mcpServers` (`string` or `object`): MCP config path, or an object whose keys are MCP server names and whose values are MCP server config objects.
|
||||||
|
- `apps` (`string`): App manifest path for plugin integrations.
|
||||||
|
- `interface` (`object`): Interface/UX metadata block for plugin presentation.
|
||||||
|
|
||||||
|
`mcpServers` may be declared as a companion file path:
|
||||||
|
|
||||||
|
```json
|
||||||
|
{
|
||||||
|
"mcpServers": "./.mcp.json"
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
|
Or as an object directly in `plugin.json`:
|
||||||
|
|
||||||
|
```json
|
||||||
|
{
|
||||||
|
"mcpServers": {
|
||||||
|
"counter": {
|
||||||
|
"type": "http",
|
||||||
|
"url": "https://sample.example/counter/mcp"
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
|
### `interface` fields
|
||||||
|
|
||||||
|
- `displayName` (`string`): User-facing title shown for the plugin.
|
||||||
|
- `shortDescription` (`string`): Brief subtitle used in compact views.
|
||||||
|
- `longDescription` (`string`): Longer description used on details screens.
|
||||||
|
- `developerName` (`string`): Human-readable publisher name.
|
||||||
|
- `category` (`string`): Plugin category bucket.
|
||||||
|
- `capabilities` (`array` of `string`): Capability list from implementation.
|
||||||
|
- `websiteURL` (`string`): Public website for the plugin.
|
||||||
|
- `privacyPolicyURL` (`string`): Privacy policy URL.
|
||||||
|
- `termsOfServiceURL` (`string`): Terms of service URL.
|
||||||
|
- `defaultPrompt` (`array` of `string`): Starter prompts shown in composer/UX context.
|
||||||
|
- Include at most 3 strings. Entries after the first 3 are ignored and will not be included.
|
||||||
|
- Each string is capped at 128 characters. Longer entries are truncated.
|
||||||
|
- Prefer short starter prompts around 50 characters so they scan well in the UI.
|
||||||
|
- `brandColor` (`string`): Theme color for the plugin card.
|
||||||
|
- `composerIcon` (`string`): Path to icon asset.
|
||||||
|
- `logo` (`string`): Path to logo asset.
|
||||||
|
- `logoDark` (`string`): Optional path to the logo asset used in dark mode.
|
||||||
|
- `screenshots` (`array` of `string`): List of screenshot asset paths.
|
||||||
|
- Screenshot entries must be PNG filenames and stored under `./assets/`.
|
||||||
|
- Keep file paths relative to plugin root.
|
||||||
|
|
||||||
|
### Path conventions and defaults
|
||||||
|
|
||||||
|
- Path values should be relative and begin with `./`.
|
||||||
|
- `skills`, `hooks`, and string-valued `mcpServers` are supplemented on top of default component discovery; they do not replace defaults.
|
||||||
|
- Custom path values must follow the plugin root convention and naming/namespacing rules.
|
||||||
|
- This repo’s scaffold writes `.codex-plugin/plugin.json`; treat that as the manifest location this skill generates.
|
||||||
|
|
||||||
|
# Marketplace JSON sample spec
|
||||||
|
|
||||||
|
`marketplace.json` depends on where the plugin should live. New plugin creation defaults to the
|
||||||
|
personal marketplace unless the caller explicitly requests a repo-local destination:
|
||||||
|
|
||||||
|
- Personal plugin: `~/.agents/plugins/marketplace.json`
|
||||||
|
- Repo/team plugin: `<repo-root>/.agents/plugins/marketplace.json`
|
||||||
|
|
||||||
|
```json
|
||||||
|
{
|
||||||
|
"name": "openai-curated",
|
||||||
|
"interface": {
|
||||||
|
"displayName": "ChatGPT Official"
|
||||||
|
},
|
||||||
|
"plugins": [
|
||||||
|
{
|
||||||
|
"name": "linear",
|
||||||
|
"source": {
|
||||||
|
"source": "local",
|
||||||
|
"path": "./plugins/linear"
|
||||||
|
},
|
||||||
|
"policy": {
|
||||||
|
"installation": "AVAILABLE",
|
||||||
|
"authentication": "ON_INSTALL"
|
||||||
|
},
|
||||||
|
"category": "Productivity"
|
||||||
|
}
|
||||||
|
]
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
|
## Marketplace field guide
|
||||||
|
|
||||||
|
### Top-level fields
|
||||||
|
|
||||||
|
- `name` (`string`): Marketplace identifier or catalog name.
|
||||||
|
- `interface` (`object`, optional): Marketplace presentation metadata.
|
||||||
|
- `plugins` (`array`): Ordered plugin entries. This order determines how Codex renders plugins.
|
||||||
|
|
||||||
|
### `interface` fields
|
||||||
|
|
||||||
|
- `displayName` (`string`, optional): User-facing marketplace title.
|
||||||
|
|
||||||
|
### Plugin entry fields
|
||||||
|
|
||||||
|
- `name` (`string`): Plugin identifier. Match the plugin folder name and `plugin.json` `name`.
|
||||||
|
- `source` (`object`): Plugin source descriptor.
|
||||||
|
- `source` (`string`): Use `local` for this repo workflow.
|
||||||
|
- `path` (`string`): Relative plugin path based on the marketplace root.
|
||||||
|
- Personal plugin in `~/.agents/plugins/marketplace.json`: `./plugins/<plugin-name>`
|
||||||
|
- Repo/team plugin: `./plugins/<plugin-name>`
|
||||||
|
- The same relative path convention is used for both personal and repo/team marketplaces.
|
||||||
|
- Example: with `~/.agents/plugins/marketplace.json`, `./plugins/<plugin-name>` resolves to
|
||||||
|
`~/plugins/<plugin-name>`.
|
||||||
|
- `policy` (`object`): Marketplace policy block. Always include it.
|
||||||
|
- `installation` (`string`): Availability policy.
|
||||||
|
- Allowed values: `NOT_AVAILABLE`, `AVAILABLE`, `INSTALLED_BY_DEFAULT`
|
||||||
|
- Default for new entries: `AVAILABLE`
|
||||||
|
- `authentication` (`string`): Authentication timing policy.
|
||||||
|
- Allowed values: `ON_INSTALL`, `ON_USE`
|
||||||
|
- Default for new entries: `ON_INSTALL`
|
||||||
|
- `products` (`array` of `string`, optional): Product override for this plugin entry. Omit it unless product gating is explicitly requested.
|
||||||
|
- `category` (`string`): Display category bucket. Always include it.
|
||||||
|
|
||||||
|
### Marketplace generation rules
|
||||||
|
|
||||||
|
- `displayName` belongs under the top-level `interface` object, not individual plugin entries.
|
||||||
|
- When creating a new marketplace file from scratch, seed `interface.displayName` alongside top-level `name`.
|
||||||
|
- Always include `policy.installation`, `policy.authentication`, and `category` on every generated or updated plugin entry.
|
||||||
|
- Treat `policy.products` as an override and omit it unless explicitly requested.
|
||||||
|
- Append new entries unless the user explicitly requests reordering.
|
||||||
|
- Replace an existing entry for the same plugin only when overwrite is intentional.
|
||||||
|
- Default new plugin creation to the personal marketplace.
|
||||||
|
- Use a repo/team marketplace only when the user specifically requests that destination.
|
||||||
|
- Only override the marketplace `name` when the default `personal` name is already taken or
|
||||||
|
installed and you need to seed a different new marketplace file.
|
||||||
|
- Choose marketplace location to match the selected destination:
|
||||||
|
- Personal plugin: `~/.agents/plugins/marketplace.json`
|
||||||
|
- Repo/team plugin: `<repo-root>/.agents/plugins/marketplace.json`
|
||||||
|
|
||||||
|
### Plugin validation notes
|
||||||
|
|
||||||
|
- The validator mirrors the workspace plugin ingestion schema so generated plugins follow the same
|
||||||
|
manifest contract from the start.
|
||||||
|
- Plugin manifests must include real values for `name`, `version`, `description`,
|
||||||
|
`author.name`, and the required `interface` fields.
|
||||||
|
- `version` must use strict semver.
|
||||||
|
- `websiteURL`, `privacyPolicyURL`, and `termsOfServiceURL` must be absolute `https://` URLs when
|
||||||
|
present.
|
||||||
|
- `composerIcon`, `logo`, `logoDark`, and `screenshots` must point to real files inside the plugin archive when
|
||||||
|
present.
|
||||||
|
- `apps` should appear in `plugin.json` only when `.app.json` actually exists.
|
||||||
|
- `mcpServers` may point to `.mcp.json` or contain the MCP server object directly in
|
||||||
|
`plugin.json`.
|
||||||
|
- Validation rejects unsupported manifest fields such as `hooks`, so the scaffold keeps them out of
|
||||||
|
generated manifests.
|
||||||
|
- Run `scripts/validate_plugin.py <plugin-path>` before handing back a generated plugin. It adds one
|
||||||
|
intentional preflight check that rejects leftover `[TODO: ...]` placeholders.
|
||||||
324
skills/.system/plugin-creator/scripts/create_basic_plugin.py
Normal file
324
skills/.system/plugin-creator/scripts/create_basic_plugin.py
Normal file
@ -0,0 +1,324 @@
|
|||||||
|
#!/usr/bin/env python3
|
||||||
|
"""Scaffold a plugin directory and optionally update marketplace.json."""
|
||||||
|
|
||||||
|
from __future__ import annotations
|
||||||
|
|
||||||
|
import argparse
|
||||||
|
import json
|
||||||
|
import re
|
||||||
|
from pathlib import Path
|
||||||
|
from typing import Any
|
||||||
|
|
||||||
|
|
||||||
|
MAX_PLUGIN_NAME_LENGTH = 64
|
||||||
|
DEFAULT_INSTALL_POLICY = "AVAILABLE"
|
||||||
|
DEFAULT_AUTH_POLICY = "ON_INSTALL"
|
||||||
|
DEFAULT_CATEGORY = "Productivity"
|
||||||
|
DEFAULT_MARKETPLACE_NAME = "personal"
|
||||||
|
VALID_INSTALL_POLICIES = {"NOT_AVAILABLE", "AVAILABLE", "INSTALLED_BY_DEFAULT"}
|
||||||
|
VALID_AUTH_POLICIES = {"ON_INSTALL", "ON_USE"}
|
||||||
|
DEFAULT_PLUGIN_PARENT = Path.home() / "plugins"
|
||||||
|
DEFAULT_MARKETPLACE_PATH = Path.home() / ".agents" / "plugins" / "marketplace.json"
|
||||||
|
|
||||||
|
|
||||||
|
def normalize_plugin_name(plugin_name: str) -> str:
|
||||||
|
"""Normalize a plugin name to lowercase hyphen-case."""
|
||||||
|
normalized = plugin_name.strip().lower()
|
||||||
|
normalized = re.sub(r"[^a-z0-9]+", "-", normalized)
|
||||||
|
normalized = normalized.strip("-")
|
||||||
|
normalized = re.sub(r"-{2,}", "-", normalized)
|
||||||
|
return normalized
|
||||||
|
|
||||||
|
|
||||||
|
def validate_plugin_name(plugin_name: str) -> None:
|
||||||
|
if not plugin_name:
|
||||||
|
raise ValueError("Plugin name must include at least one letter or digit.")
|
||||||
|
if len(plugin_name) > MAX_PLUGIN_NAME_LENGTH:
|
||||||
|
raise ValueError(
|
||||||
|
f"Plugin name '{plugin_name}' is too long ({len(plugin_name)} characters). "
|
||||||
|
f"Maximum is {MAX_PLUGIN_NAME_LENGTH} characters."
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
def validate_marketplace_name(marketplace_name: str) -> None:
|
||||||
|
if not marketplace_name:
|
||||||
|
raise ValueError("Marketplace name must include at least one letter or digit.")
|
||||||
|
if re.fullmatch(r"[A-Za-z0-9_-]+", marketplace_name) is None:
|
||||||
|
raise ValueError(
|
||||||
|
"Marketplace name may only contain ASCII letters, digits, `_`, and `-`."
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
def display_name_from_plugin_name(plugin_name: str) -> str:
|
||||||
|
return " ".join(part.capitalize() for part in re.split(r"[-_]+", plugin_name))
|
||||||
|
|
||||||
|
|
||||||
|
def build_plugin_json(plugin_name: str, *, with_mcp: bool, with_apps: bool) -> dict[str, Any]:
|
||||||
|
display_name = display_name_from_plugin_name(plugin_name)
|
||||||
|
payload: dict[str, Any] = {
|
||||||
|
"name": plugin_name,
|
||||||
|
"version": "0.1.0",
|
||||||
|
"description": f"{display_name} plugin",
|
||||||
|
"author": {
|
||||||
|
"name": "Local developer",
|
||||||
|
},
|
||||||
|
"skills": "./skills/",
|
||||||
|
"interface": {
|
||||||
|
"displayName": display_name,
|
||||||
|
"shortDescription": f"Use {display_name} in Codex.",
|
||||||
|
"longDescription": f"{display_name} adds a local Codex plugin scaffold.",
|
||||||
|
"developerName": "Local developer",
|
||||||
|
"category": DEFAULT_CATEGORY,
|
||||||
|
"capabilities": [],
|
||||||
|
"defaultPrompt": f"Help me use {display_name}.",
|
||||||
|
},
|
||||||
|
}
|
||||||
|
if with_mcp:
|
||||||
|
payload["mcpServers"] = "./.mcp.json"
|
||||||
|
if with_apps:
|
||||||
|
payload["apps"] = "./.app.json"
|
||||||
|
return payload
|
||||||
|
|
||||||
|
|
||||||
|
def build_marketplace_entry(
|
||||||
|
plugin_name: str,
|
||||||
|
install_policy: str,
|
||||||
|
auth_policy: str,
|
||||||
|
category: str,
|
||||||
|
) -> dict[str, Any]:
|
||||||
|
return {
|
||||||
|
"name": plugin_name,
|
||||||
|
"source": {
|
||||||
|
"source": "local",
|
||||||
|
"path": f"./plugins/{plugin_name}",
|
||||||
|
},
|
||||||
|
"policy": {
|
||||||
|
"installation": install_policy,
|
||||||
|
"authentication": auth_policy,
|
||||||
|
},
|
||||||
|
"category": category,
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
def load_json(path: Path) -> dict[str, Any]:
|
||||||
|
with path.open() as handle:
|
||||||
|
return json.load(handle)
|
||||||
|
|
||||||
|
|
||||||
|
def build_default_marketplace(marketplace_name: str) -> dict[str, Any]:
|
||||||
|
return {
|
||||||
|
"name": marketplace_name,
|
||||||
|
"interface": {
|
||||||
|
"displayName": display_name_from_plugin_name(marketplace_name),
|
||||||
|
},
|
||||||
|
"plugins": [],
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
def validate_marketplace_interface(payload: dict[str, Any]) -> None:
|
||||||
|
interface = payload.get("interface")
|
||||||
|
if interface is not None and not isinstance(interface, dict):
|
||||||
|
raise ValueError("marketplace.json field 'interface' must be an object.")
|
||||||
|
|
||||||
|
|
||||||
|
def update_marketplace_json(
|
||||||
|
marketplace_path: Path,
|
||||||
|
marketplace_name: str | None,
|
||||||
|
plugin_name: str,
|
||||||
|
install_policy: str,
|
||||||
|
auth_policy: str,
|
||||||
|
category: str,
|
||||||
|
force: bool,
|
||||||
|
) -> None:
|
||||||
|
if marketplace_path.exists():
|
||||||
|
payload = load_json(marketplace_path)
|
||||||
|
else:
|
||||||
|
payload = build_default_marketplace(marketplace_name or DEFAULT_MARKETPLACE_NAME)
|
||||||
|
|
||||||
|
if not isinstance(payload, dict):
|
||||||
|
raise ValueError(f"{marketplace_path} must contain a JSON object.")
|
||||||
|
|
||||||
|
validate_marketplace_interface(payload)
|
||||||
|
|
||||||
|
existing_marketplace_name = payload.get("name")
|
||||||
|
if marketplace_name is not None:
|
||||||
|
if not isinstance(existing_marketplace_name, str) or not existing_marketplace_name.strip():
|
||||||
|
raise ValueError(f"{marketplace_path} must contain a non-empty string 'name'.")
|
||||||
|
if existing_marketplace_name != marketplace_name:
|
||||||
|
raise ValueError(
|
||||||
|
f"{marketplace_path} already uses marketplace name "
|
||||||
|
f"'{existing_marketplace_name}'. Create a new marketplace file to use "
|
||||||
|
f"'{marketplace_name}' instead."
|
||||||
|
)
|
||||||
|
|
||||||
|
plugins = payload.setdefault("plugins", [])
|
||||||
|
if not isinstance(plugins, list):
|
||||||
|
raise ValueError(f"{marketplace_path} field 'plugins' must be an array.")
|
||||||
|
|
||||||
|
new_entry = build_marketplace_entry(plugin_name, install_policy, auth_policy, category)
|
||||||
|
|
||||||
|
for index, entry in enumerate(plugins):
|
||||||
|
if isinstance(entry, dict) and entry.get("name") == plugin_name:
|
||||||
|
if not force:
|
||||||
|
raise FileExistsError(
|
||||||
|
f"Marketplace entry '{plugin_name}' already exists in {marketplace_path}. "
|
||||||
|
"Use --force to overwrite that entry."
|
||||||
|
)
|
||||||
|
plugins[index] = new_entry
|
||||||
|
break
|
||||||
|
else:
|
||||||
|
plugins.append(new_entry)
|
||||||
|
|
||||||
|
write_json(marketplace_path, payload, force=True)
|
||||||
|
|
||||||
|
|
||||||
|
def write_json(path: Path, data: dict, force: bool) -> None:
|
||||||
|
if path.exists() and not force:
|
||||||
|
raise FileExistsError(f"{path} already exists. Use --force to overwrite.")
|
||||||
|
path.parent.mkdir(parents=True, exist_ok=True)
|
||||||
|
with path.open("w") as handle:
|
||||||
|
json.dump(data, handle, indent=2)
|
||||||
|
handle.write("\n")
|
||||||
|
|
||||||
|
|
||||||
|
def create_stub_file(path: Path, payload: dict, force: bool) -> None:
|
||||||
|
if path.exists() and not force:
|
||||||
|
return
|
||||||
|
path.parent.mkdir(parents=True, exist_ok=True)
|
||||||
|
with path.open("w") as handle:
|
||||||
|
json.dump(payload, handle, indent=2)
|
||||||
|
handle.write("\n")
|
||||||
|
|
||||||
|
|
||||||
|
def parse_args() -> argparse.Namespace:
|
||||||
|
parser = argparse.ArgumentParser(
|
||||||
|
description="Create a plugin skeleton with a validation-ready plugin.json."
|
||||||
|
)
|
||||||
|
parser.add_argument("plugin_name")
|
||||||
|
parser.add_argument(
|
||||||
|
"--path",
|
||||||
|
default=str(DEFAULT_PLUGIN_PARENT),
|
||||||
|
help=(
|
||||||
|
"Parent directory for plugin creation (defaults to <home>/plugins). "
|
||||||
|
"Pass an explicit repo path only when a repo/team plugin is intended."
|
||||||
|
),
|
||||||
|
)
|
||||||
|
parser.add_argument("--with-skills", action="store_true", help="Create skills/ directory")
|
||||||
|
parser.add_argument("--with-hooks", action="store_true", help="Create hooks/ directory")
|
||||||
|
parser.add_argument("--with-scripts", action="store_true", help="Create scripts/ directory")
|
||||||
|
parser.add_argument("--with-assets", action="store_true", help="Create assets/ directory")
|
||||||
|
parser.add_argument("--with-mcp", action="store_true", help="Create .mcp.json placeholder")
|
||||||
|
parser.add_argument("--with-apps", action="store_true", help="Create .app.json placeholder")
|
||||||
|
parser.add_argument(
|
||||||
|
"--with-marketplace",
|
||||||
|
action="store_true",
|
||||||
|
help=(
|
||||||
|
"Create or update <home>/.agents/plugins/marketplace.json by default. "
|
||||||
|
"Marketplace entries always point to ./plugins/<plugin-name> relative to the "
|
||||||
|
"marketplace root."
|
||||||
|
),
|
||||||
|
)
|
||||||
|
parser.add_argument(
|
||||||
|
"--marketplace-path",
|
||||||
|
default=str(DEFAULT_MARKETPLACE_PATH),
|
||||||
|
help=(
|
||||||
|
"Path to marketplace.json (defaults to <home>/.agents/plugins/marketplace.json). "
|
||||||
|
"Pass a repo-rooted marketplace path only when a repo/team plugin is intended."
|
||||||
|
),
|
||||||
|
)
|
||||||
|
parser.add_argument(
|
||||||
|
"--marketplace-name",
|
||||||
|
help=(
|
||||||
|
"Marketplace name to seed into a new marketplace.json. Use this only when the default "
|
||||||
|
"'personal' marketplace name is already taken and you need a different new marketplace."
|
||||||
|
),
|
||||||
|
)
|
||||||
|
parser.add_argument(
|
||||||
|
"--install-policy",
|
||||||
|
default=DEFAULT_INSTALL_POLICY,
|
||||||
|
choices=sorted(VALID_INSTALL_POLICIES),
|
||||||
|
help="Marketplace policy.installation value",
|
||||||
|
)
|
||||||
|
parser.add_argument(
|
||||||
|
"--auth-policy",
|
||||||
|
default=DEFAULT_AUTH_POLICY,
|
||||||
|
choices=sorted(VALID_AUTH_POLICIES),
|
||||||
|
help="Marketplace policy.authentication value",
|
||||||
|
)
|
||||||
|
parser.add_argument(
|
||||||
|
"--category",
|
||||||
|
default=DEFAULT_CATEGORY,
|
||||||
|
help="Marketplace category value",
|
||||||
|
)
|
||||||
|
parser.add_argument("--force", action="store_true", help="Overwrite existing files")
|
||||||
|
return parser.parse_args()
|
||||||
|
|
||||||
|
|
||||||
|
def main() -> None:
|
||||||
|
args = parse_args()
|
||||||
|
raw_plugin_name = args.plugin_name
|
||||||
|
plugin_name = normalize_plugin_name(raw_plugin_name)
|
||||||
|
if plugin_name != raw_plugin_name:
|
||||||
|
print(f"Note: Normalized plugin name from '{raw_plugin_name}' to '{plugin_name}'.")
|
||||||
|
validate_plugin_name(plugin_name)
|
||||||
|
marketplace_name = None
|
||||||
|
if args.marketplace_name is not None:
|
||||||
|
marketplace_name = args.marketplace_name.strip()
|
||||||
|
validate_marketplace_name(marketplace_name)
|
||||||
|
|
||||||
|
plugin_root = (Path(args.path).expanduser().resolve() / plugin_name)
|
||||||
|
plugin_root.mkdir(parents=True, exist_ok=True)
|
||||||
|
|
||||||
|
plugin_json_path = plugin_root / ".codex-plugin" / "plugin.json"
|
||||||
|
write_json(
|
||||||
|
plugin_json_path,
|
||||||
|
build_plugin_json(plugin_name, with_mcp=args.with_mcp, with_apps=args.with_apps),
|
||||||
|
args.force,
|
||||||
|
)
|
||||||
|
|
||||||
|
optional_directories = {
|
||||||
|
"skills": args.with_skills,
|
||||||
|
"hooks": args.with_hooks,
|
||||||
|
"scripts": args.with_scripts,
|
||||||
|
"assets": args.with_assets,
|
||||||
|
}
|
||||||
|
for folder, enabled in optional_directories.items():
|
||||||
|
if enabled:
|
||||||
|
(plugin_root / folder).mkdir(parents=True, exist_ok=True)
|
||||||
|
|
||||||
|
if args.with_mcp:
|
||||||
|
create_stub_file(
|
||||||
|
plugin_root / ".mcp.json",
|
||||||
|
{"mcpServers": {}},
|
||||||
|
args.force,
|
||||||
|
)
|
||||||
|
|
||||||
|
if args.with_apps:
|
||||||
|
create_stub_file(
|
||||||
|
plugin_root / ".app.json",
|
||||||
|
{
|
||||||
|
"apps": {},
|
||||||
|
},
|
||||||
|
args.force,
|
||||||
|
)
|
||||||
|
|
||||||
|
if args.with_marketplace:
|
||||||
|
marketplace_path = Path(args.marketplace_path).expanduser().resolve()
|
||||||
|
update_marketplace_json(
|
||||||
|
marketplace_path,
|
||||||
|
marketplace_name,
|
||||||
|
plugin_name,
|
||||||
|
args.install_policy,
|
||||||
|
args.auth_policy,
|
||||||
|
args.category,
|
||||||
|
args.force,
|
||||||
|
)
|
||||||
|
|
||||||
|
print(f"Created plugin scaffold: {plugin_root}")
|
||||||
|
print(f"plugin manifest: {plugin_json_path}")
|
||||||
|
if args.with_marketplace:
|
||||||
|
print(f"marketplace manifest: {marketplace_path}")
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
main()
|
||||||
@ -0,0 +1,48 @@
|
|||||||
|
#!/usr/bin/env python3
|
||||||
|
"""Print the top-level marketplace name from any marketplace.json file."""
|
||||||
|
|
||||||
|
from __future__ import annotations
|
||||||
|
|
||||||
|
import argparse
|
||||||
|
import json
|
||||||
|
import sys
|
||||||
|
from pathlib import Path
|
||||||
|
|
||||||
|
|
||||||
|
def default_marketplace_path() -> Path:
|
||||||
|
return Path.home() / ".agents" / "plugins" / "marketplace.json"
|
||||||
|
|
||||||
|
|
||||||
|
def parse_args() -> argparse.Namespace:
|
||||||
|
parser = argparse.ArgumentParser(
|
||||||
|
description=(
|
||||||
|
"Print the top-level marketplace name from marketplace.json. Defaults to the personal "
|
||||||
|
"marketplace path under the current home directory."
|
||||||
|
)
|
||||||
|
)
|
||||||
|
parser.add_argument(
|
||||||
|
"--marketplace-path",
|
||||||
|
default=str(default_marketplace_path()),
|
||||||
|
help="Path to marketplace.json",
|
||||||
|
)
|
||||||
|
return parser.parse_args()
|
||||||
|
|
||||||
|
|
||||||
|
def main() -> None:
|
||||||
|
args = parse_args()
|
||||||
|
marketplace_path = Path(args.marketplace_path).expanduser().resolve()
|
||||||
|
payload = json.loads(marketplace_path.read_text(encoding="utf-8"))
|
||||||
|
if not isinstance(payload, dict):
|
||||||
|
raise ValueError(f"{marketplace_path} must contain a JSON object.")
|
||||||
|
name = payload.get("name")
|
||||||
|
if not isinstance(name, str) or not name.strip():
|
||||||
|
raise ValueError(f"{marketplace_path} must contain a non-empty string 'name'.")
|
||||||
|
print(name.strip())
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
try:
|
||||||
|
main()
|
||||||
|
except Exception as err: # noqa: BLE001 - CLI should surface a single clear message.
|
||||||
|
print(str(err), file=sys.stderr)
|
||||||
|
raise SystemExit(1) from err
|
||||||
@ -0,0 +1,78 @@
|
|||||||
|
#!/usr/bin/env python3
|
||||||
|
"""Rewrite a local plugin version to a single Codex cachebuster suffix."""
|
||||||
|
|
||||||
|
from __future__ import annotations
|
||||||
|
|
||||||
|
import argparse
|
||||||
|
import json
|
||||||
|
import re
|
||||||
|
import sys
|
||||||
|
from datetime import datetime, timezone
|
||||||
|
from pathlib import Path
|
||||||
|
|
||||||
|
|
||||||
|
CACHEBUSTER_PREFIX = "codex"
|
||||||
|
|
||||||
|
|
||||||
|
def parse_args() -> argparse.Namespace:
|
||||||
|
parser = argparse.ArgumentParser(
|
||||||
|
description=(
|
||||||
|
"Rewrite a local plugin's version so it preserves everything before '+' and uses "
|
||||||
|
"a single +codex.<cachebuster> suffix."
|
||||||
|
)
|
||||||
|
)
|
||||||
|
parser.add_argument("plugin_path", help="Path to the plugin root directory")
|
||||||
|
parser.add_argument(
|
||||||
|
"--cachebuster",
|
||||||
|
help="Optional cachebuster token to embed in the plugin version",
|
||||||
|
)
|
||||||
|
return parser.parse_args()
|
||||||
|
|
||||||
|
|
||||||
|
def main() -> None:
|
||||||
|
args = parse_args()
|
||||||
|
plugin_root = Path(args.plugin_path).expanduser().resolve()
|
||||||
|
manifest_path = plugin_root / ".codex-plugin" / "plugin.json"
|
||||||
|
manifest = load_manifest(manifest_path)
|
||||||
|
|
||||||
|
version = manifest.get("version")
|
||||||
|
if not isinstance(version, str) or not version.strip():
|
||||||
|
raise ValueError(f"{manifest_path} must contain a non-empty string 'version'.")
|
||||||
|
cachebuster = sanitize_cachebuster(args.cachebuster or default_cachebuster())
|
||||||
|
next_version = with_cachebuster(version, cachebuster)
|
||||||
|
manifest["version"] = next_version
|
||||||
|
manifest_path.write_text(json.dumps(manifest, indent=2) + "\n", encoding="utf-8")
|
||||||
|
|
||||||
|
print(f"Updated plugin version: {version} -> {next_version}")
|
||||||
|
|
||||||
|
|
||||||
|
def load_manifest(manifest_path: Path) -> dict[str, object]:
|
||||||
|
if not manifest_path.is_file():
|
||||||
|
raise FileNotFoundError(f"missing manifest: {manifest_path}")
|
||||||
|
payload = json.loads(manifest_path.read_text(encoding="utf-8"))
|
||||||
|
if not isinstance(payload, dict):
|
||||||
|
raise ValueError(f"{manifest_path} must contain a JSON object.")
|
||||||
|
return payload
|
||||||
|
def sanitize_cachebuster(value: str) -> str:
|
||||||
|
sanitized = re.sub(r"[^a-z0-9-]+", "-", value.strip().lower())
|
||||||
|
sanitized = re.sub(r"-{2,}", "-", sanitized).strip("-")
|
||||||
|
if not sanitized:
|
||||||
|
raise ValueError("Cachebuster must contain at least one letter or digit.")
|
||||||
|
return sanitized
|
||||||
|
|
||||||
|
|
||||||
|
def default_cachebuster() -> str:
|
||||||
|
return datetime.now(timezone.utc).strftime("%Y%m%d%H%M%S")
|
||||||
|
|
||||||
|
|
||||||
|
def with_cachebuster(version: str, cachebuster: str) -> str:
|
||||||
|
version_prefix = version.split("+", 1)[0]
|
||||||
|
return f"{version_prefix}+{CACHEBUSTER_PREFIX}.{cachebuster}"
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
try:
|
||||||
|
main()
|
||||||
|
except Exception as err: # noqa: BLE001 - CLI should surface a single clear message.
|
||||||
|
print(str(err), file=sys.stderr)
|
||||||
|
raise SystemExit(1) from err
|
||||||
629
skills/.system/plugin-creator/scripts/validate_plugin.py
Normal file
629
skills/.system/plugin-creator/scripts/validate_plugin.py
Normal file
@ -0,0 +1,629 @@
|
|||||||
|
#!/usr/bin/env python3
|
||||||
|
"""Validate a generated plugin against the plugin ingestion contract."""
|
||||||
|
|
||||||
|
from __future__ import annotations
|
||||||
|
|
||||||
|
import argparse
|
||||||
|
import json
|
||||||
|
import re
|
||||||
|
from pathlib import Path, PurePosixPath
|
||||||
|
from typing import Any
|
||||||
|
from urllib.parse import urlparse
|
||||||
|
|
||||||
|
import yaml
|
||||||
|
|
||||||
|
|
||||||
|
TODO_MARKER = "[TODO:"
|
||||||
|
SEMVER_RE = re.compile(
|
||||||
|
r"^(0|[1-9]\d*)\."
|
||||||
|
r"(0|[1-9]\d*)\."
|
||||||
|
r"(0|[1-9]\d*)"
|
||||||
|
r"(?:-(?:0|[1-9]\d*|\d*[A-Za-z-][0-9A-Za-z-]*)(?:\."
|
||||||
|
r"(?:0|[1-9]\d*|\d*[A-Za-z-][0-9A-Za-z-]*))*)?"
|
||||||
|
r"(?:\+[0-9A-Za-z-]+(?:\.[0-9A-Za-z-]+)*)?$"
|
||||||
|
)
|
||||||
|
HEX_COLOR_RE = re.compile(r"^#[0-9A-F]{6}$", re.IGNORECASE)
|
||||||
|
|
||||||
|
|
||||||
|
def parse_args() -> argparse.Namespace:
|
||||||
|
parser = argparse.ArgumentParser(description="Validate a local Codex plugin.")
|
||||||
|
parser.add_argument("plugin_path", help="Path to the plugin root directory")
|
||||||
|
return parser.parse_args()
|
||||||
|
|
||||||
|
|
||||||
|
def main() -> None:
|
||||||
|
args = parse_args()
|
||||||
|
plugin_root = Path(args.plugin_path).expanduser().resolve()
|
||||||
|
errors = validate_plugin(plugin_root)
|
||||||
|
if errors:
|
||||||
|
print("Plugin validation failed:")
|
||||||
|
for error in errors:
|
||||||
|
print(f"- {error}")
|
||||||
|
raise SystemExit(1)
|
||||||
|
print(f"Plugin validation passed: {plugin_root}")
|
||||||
|
|
||||||
|
|
||||||
|
def validate_plugin(plugin_root: Path) -> list[str]:
|
||||||
|
errors: list[str] = []
|
||||||
|
manifest_path = plugin_root / ".codex-plugin" / "plugin.json"
|
||||||
|
manifest = load_json_object(manifest_path, errors)
|
||||||
|
if manifest is None:
|
||||||
|
return errors
|
||||||
|
|
||||||
|
reject_todo_markers(manifest, "$", errors)
|
||||||
|
validate_manifest_shape(plugin_root, manifest, errors)
|
||||||
|
return errors
|
||||||
|
|
||||||
|
|
||||||
|
def load_json_object(path: Path, errors: list[str]) -> dict[str, Any] | None:
|
||||||
|
if not path.is_file():
|
||||||
|
errors.append("missing `.codex-plugin/plugin.json`")
|
||||||
|
return None
|
||||||
|
try:
|
||||||
|
payload = json.loads(path.read_text(encoding="utf-8"))
|
||||||
|
except OSError:
|
||||||
|
errors.append("unable to read `.codex-plugin/plugin.json`")
|
||||||
|
return None
|
||||||
|
except json.JSONDecodeError:
|
||||||
|
errors.append("`.codex-plugin/plugin.json` must be valid JSON")
|
||||||
|
return None
|
||||||
|
if not isinstance(payload, dict):
|
||||||
|
errors.append("`.codex-plugin/plugin.json` must contain a JSON object")
|
||||||
|
return None
|
||||||
|
return payload
|
||||||
|
|
||||||
|
|
||||||
|
def reject_todo_markers(value: Any, path: str, errors: list[str]) -> None:
|
||||||
|
if isinstance(value, str):
|
||||||
|
if TODO_MARKER in value:
|
||||||
|
errors.append(f"{path} still contains a `[TODO: ...]` placeholder")
|
||||||
|
return
|
||||||
|
if isinstance(value, list):
|
||||||
|
for index, item in enumerate(value):
|
||||||
|
reject_todo_markers(item, f"{path}[{index}]", errors)
|
||||||
|
return
|
||||||
|
if isinstance(value, dict):
|
||||||
|
for key, item in value.items():
|
||||||
|
reject_todo_markers(item, f"{path}.{key}", errors)
|
||||||
|
|
||||||
|
|
||||||
|
def validate_manifest_shape(
|
||||||
|
plugin_root: Path,
|
||||||
|
manifest: dict[str, Any],
|
||||||
|
errors: list[str],
|
||||||
|
) -> None:
|
||||||
|
allowed_keys = {
|
||||||
|
"id",
|
||||||
|
"name",
|
||||||
|
"version",
|
||||||
|
"description",
|
||||||
|
"skills",
|
||||||
|
"apps",
|
||||||
|
"mcpServers",
|
||||||
|
"interface",
|
||||||
|
"author",
|
||||||
|
"homepage",
|
||||||
|
"repository",
|
||||||
|
"license",
|
||||||
|
"keywords",
|
||||||
|
}
|
||||||
|
for key in sorted(set(manifest) - allowed_keys):
|
||||||
|
errors.append(f"plugin.json field `{key}` is not accepted by plugin validation")
|
||||||
|
|
||||||
|
validate_optional_non_empty_string(manifest, "id", errors)
|
||||||
|
require_non_empty_string(manifest, "name", errors)
|
||||||
|
version = require_non_empty_string(manifest, "version", errors)
|
||||||
|
if version is not None and SEMVER_RE.fullmatch(version) is None:
|
||||||
|
errors.append("plugin.json field `version` must be strict semver")
|
||||||
|
require_non_empty_string(manifest, "description", errors)
|
||||||
|
|
||||||
|
author = require_object(manifest, "author", errors)
|
||||||
|
if author is not None:
|
||||||
|
reject_unknown_fields(author, {"name", "email", "url"}, "author", errors)
|
||||||
|
require_non_empty_string(author, "name", errors, prefix="author")
|
||||||
|
validate_optional_non_empty_string(author, "email", errors, prefix="author")
|
||||||
|
validate_optional_https_url(author, "url", errors, prefix="author")
|
||||||
|
|
||||||
|
validate_optional_contract_path(manifest, "skills", "skills", errors)
|
||||||
|
validate_optional_contract_path(manifest, "apps", ".app.json", errors)
|
||||||
|
validate_manifest_mcp_servers(plugin_root, manifest, errors)
|
||||||
|
|
||||||
|
if manifest.get("apps") is not None:
|
||||||
|
validate_app_manifest(
|
||||||
|
plugin_root / ".app.json",
|
||||||
|
errors,
|
||||||
|
)
|
||||||
|
validate_skill_manifests(plugin_root, errors)
|
||||||
|
|
||||||
|
interface = require_object(manifest, "interface", errors)
|
||||||
|
if interface is None:
|
||||||
|
return
|
||||||
|
reject_unknown_fields(
|
||||||
|
interface,
|
||||||
|
{
|
||||||
|
"displayName",
|
||||||
|
"shortDescription",
|
||||||
|
"longDescription",
|
||||||
|
"developerName",
|
||||||
|
"category",
|
||||||
|
"capabilities",
|
||||||
|
"websiteURL",
|
||||||
|
"privacyPolicyURL",
|
||||||
|
"termsOfServiceURL",
|
||||||
|
"brandColor",
|
||||||
|
"composerIcon",
|
||||||
|
"logo",
|
||||||
|
"logoDark",
|
||||||
|
"screenshots",
|
||||||
|
"defaultPrompt",
|
||||||
|
"default_prompt",
|
||||||
|
},
|
||||||
|
"interface",
|
||||||
|
errors,
|
||||||
|
)
|
||||||
|
for field in (
|
||||||
|
"displayName",
|
||||||
|
"shortDescription",
|
||||||
|
"longDescription",
|
||||||
|
"developerName",
|
||||||
|
"category",
|
||||||
|
):
|
||||||
|
require_non_empty_string(interface, field, errors, prefix="interface")
|
||||||
|
if "defaultPrompt" not in interface and "default_prompt" not in interface:
|
||||||
|
errors.append(
|
||||||
|
"plugin.json field `interface.defaultPrompt` or `interface.default_prompt` is required"
|
||||||
|
)
|
||||||
|
capabilities = interface.get("capabilities")
|
||||||
|
if not isinstance(capabilities, list) or not all(
|
||||||
|
isinstance(value, str) and value.strip() for value in capabilities
|
||||||
|
):
|
||||||
|
errors.append("plugin.json field `interface.capabilities` must be an array of strings")
|
||||||
|
for field in ("websiteURL", "privacyPolicyURL", "termsOfServiceURL"):
|
||||||
|
validate_optional_https_url(interface, field, errors, prefix="interface")
|
||||||
|
brand_color = interface.get("brandColor")
|
||||||
|
if brand_color is not None and (
|
||||||
|
not isinstance(brand_color, str) or HEX_COLOR_RE.fullmatch(brand_color) is None
|
||||||
|
):
|
||||||
|
errors.append("plugin.json field `interface.brandColor` must use `#RRGGBB`")
|
||||||
|
for field in ("composerIcon", "logo", "logoDark"):
|
||||||
|
validate_optional_asset_path(plugin_root, plugin_root, interface, field, errors)
|
||||||
|
screenshots = interface.get("screenshots", [])
|
||||||
|
if not isinstance(screenshots, list):
|
||||||
|
errors.append("plugin.json field `interface.screenshots` must be an array")
|
||||||
|
else:
|
||||||
|
for index, raw_path in enumerate(screenshots):
|
||||||
|
validate_asset_path(
|
||||||
|
plugin_root,
|
||||||
|
plugin_root,
|
||||||
|
raw_path,
|
||||||
|
f"interface.screenshots[{index}]",
|
||||||
|
errors,
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
def require_object(
|
||||||
|
payload: dict[str, Any],
|
||||||
|
key: str,
|
||||||
|
errors: list[str],
|
||||||
|
) -> dict[str, Any] | None:
|
||||||
|
value = payload.get(key)
|
||||||
|
if not isinstance(value, dict):
|
||||||
|
errors.append(f"plugin.json field `{key}` must be an object")
|
||||||
|
return None
|
||||||
|
return value
|
||||||
|
|
||||||
|
|
||||||
|
def require_non_empty_string(
|
||||||
|
payload: dict[str, Any],
|
||||||
|
key: str,
|
||||||
|
errors: list[str],
|
||||||
|
*,
|
||||||
|
prefix: str | None = None,
|
||||||
|
) -> str | None:
|
||||||
|
value = payload.get(key)
|
||||||
|
field = f"{prefix}.{key}" if prefix is not None else key
|
||||||
|
if not isinstance(value, str) or not value.strip():
|
||||||
|
errors.append(f"plugin.json field `{field}` must be a non-empty string")
|
||||||
|
return None
|
||||||
|
return value
|
||||||
|
|
||||||
|
|
||||||
|
def validate_optional_non_empty_string(
|
||||||
|
payload: dict[str, Any],
|
||||||
|
key: str,
|
||||||
|
errors: list[str],
|
||||||
|
*,
|
||||||
|
prefix: str | None = None,
|
||||||
|
) -> None:
|
||||||
|
value = payload.get(key)
|
||||||
|
if value is None:
|
||||||
|
return
|
||||||
|
field = f"{prefix}.{key}" if prefix is not None else key
|
||||||
|
if not isinstance(value, str) or not value.strip():
|
||||||
|
errors.append(f"plugin.json field `{field}` must be a non-empty string")
|
||||||
|
|
||||||
|
|
||||||
|
def reject_unknown_fields(
|
||||||
|
payload: dict[str, Any],
|
||||||
|
allowed_keys: set[str],
|
||||||
|
prefix: str,
|
||||||
|
errors: list[str],
|
||||||
|
) -> None:
|
||||||
|
for key in sorted(set(payload) - allowed_keys):
|
||||||
|
errors.append(f"plugin.json field `{prefix}.{key}` is not accepted by plugin validation")
|
||||||
|
|
||||||
|
|
||||||
|
def validate_optional_https_url(
|
||||||
|
payload: dict[str, Any],
|
||||||
|
key: str,
|
||||||
|
errors: list[str],
|
||||||
|
*,
|
||||||
|
prefix: str,
|
||||||
|
) -> None:
|
||||||
|
value = payload.get(key)
|
||||||
|
if value is None:
|
||||||
|
return
|
||||||
|
parsed = urlparse(value) if isinstance(value, str) else None
|
||||||
|
if parsed is None or parsed.scheme != "https" or not parsed.netloc:
|
||||||
|
errors.append(f"plugin.json field `{prefix}.{key}` must be an absolute `https://` URL")
|
||||||
|
|
||||||
|
|
||||||
|
def validate_optional_contract_path(
|
||||||
|
payload: dict[str, Any],
|
||||||
|
key: str,
|
||||||
|
expected: str,
|
||||||
|
errors: list[str],
|
||||||
|
) -> None:
|
||||||
|
value = payload.get(key)
|
||||||
|
if value is None:
|
||||||
|
return
|
||||||
|
normalized = normalize_contract_path(value) if isinstance(value, str) else None
|
||||||
|
if normalized != expected:
|
||||||
|
errors.append(f"plugin.json field `{key}` must resolve to `{expected}`")
|
||||||
|
|
||||||
|
|
||||||
|
def validate_manifest_mcp_servers(
|
||||||
|
plugin_root: Path,
|
||||||
|
manifest: dict[str, Any],
|
||||||
|
errors: list[str],
|
||||||
|
) -> None:
|
||||||
|
value = manifest.get("mcpServers")
|
||||||
|
if value is None:
|
||||||
|
return
|
||||||
|
if isinstance(value, str):
|
||||||
|
validate_optional_contract_path(manifest, "mcpServers", ".mcp.json", errors)
|
||||||
|
validate_mcp_manifest(
|
||||||
|
plugin_root / ".mcp.json",
|
||||||
|
errors,
|
||||||
|
)
|
||||||
|
return
|
||||||
|
if isinstance(value, dict):
|
||||||
|
validate_mcp_server_entries(
|
||||||
|
value,
|
||||||
|
"plugin.json field `mcpServers`",
|
||||||
|
"plugin.json field `mcpServers`",
|
||||||
|
errors,
|
||||||
|
)
|
||||||
|
return
|
||||||
|
errors.append("plugin.json field `mcpServers` must be a string path or object")
|
||||||
|
|
||||||
|
|
||||||
|
def normalize_contract_path(raw_path: str) -> str | None:
|
||||||
|
path = Path(raw_path)
|
||||||
|
if path.is_absolute():
|
||||||
|
return None
|
||||||
|
normalized = path.as_posix().rstrip("/")
|
||||||
|
return normalized or None
|
||||||
|
|
||||||
|
|
||||||
|
def validate_app_manifest(path: Path, errors: list[str]) -> None:
|
||||||
|
payload = load_companion_json_object(path, "`.app.json`", errors)
|
||||||
|
if payload is None:
|
||||||
|
return
|
||||||
|
reject_companion_unknown_fields(payload, {"apps"}, "`.app.json`", errors)
|
||||||
|
apps = payload.get("apps")
|
||||||
|
if not isinstance(apps, dict):
|
||||||
|
errors.append("`.app.json` field `apps` must be an object")
|
||||||
|
return
|
||||||
|
for key, value in apps.items():
|
||||||
|
if not isinstance(value, dict):
|
||||||
|
errors.append(f"`.app.json` app `{key}` must be an object")
|
||||||
|
continue
|
||||||
|
reject_companion_unknown_fields(
|
||||||
|
value, {"id", "category"}, f"`.app.json` app `{key}`", errors
|
||||||
|
)
|
||||||
|
app_id = value.get("id")
|
||||||
|
if not isinstance(app_id, str) or not app_id.strip():
|
||||||
|
errors.append(f"`.app.json` app `{key}` field `id` must be a non-empty string")
|
||||||
|
category = value.get("category")
|
||||||
|
if category is not None and (not isinstance(category, str) or not category.strip()):
|
||||||
|
errors.append(
|
||||||
|
f"`.app.json` app `{key}` field `category` must be a non-empty string"
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
def validate_mcp_manifest(path: Path, errors: list[str]) -> None:
|
||||||
|
payload = load_companion_json_object(path, "`.mcp.json`", errors)
|
||||||
|
if payload is None:
|
||||||
|
return
|
||||||
|
reject_companion_unknown_fields(payload, {"mcpServers"}, "`.mcp.json`", errors)
|
||||||
|
servers = payload.get("mcpServers")
|
||||||
|
validate_mcp_server_entries(
|
||||||
|
servers,
|
||||||
|
"`.mcp.json`",
|
||||||
|
"`.mcp.json` field `mcpServers`",
|
||||||
|
errors,
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
def validate_mcp_server_entries(
|
||||||
|
servers: Any,
|
||||||
|
source_label: str,
|
||||||
|
field_label: str,
|
||||||
|
errors: list[str],
|
||||||
|
) -> None:
|
||||||
|
if not isinstance(servers, dict):
|
||||||
|
errors.append(f"{field_label} must be an object")
|
||||||
|
return
|
||||||
|
for key, value in servers.items():
|
||||||
|
if not isinstance(key, str) or not key.strip():
|
||||||
|
errors.append(f"{source_label} server names must be non-empty strings")
|
||||||
|
if not isinstance(value, dict):
|
||||||
|
errors.append(f"{source_label} server `{key}` must be an object")
|
||||||
|
|
||||||
|
|
||||||
|
def load_companion_json_object(
|
||||||
|
path: Path,
|
||||||
|
label: str,
|
||||||
|
errors: list[str],
|
||||||
|
) -> dict[str, Any] | None:
|
||||||
|
if not path.is_file():
|
||||||
|
errors.append(f"{label} is required when its plugin.json field is present")
|
||||||
|
return None
|
||||||
|
try:
|
||||||
|
payload = json.loads(path.read_text(encoding="utf-8"))
|
||||||
|
except (OSError, json.JSONDecodeError):
|
||||||
|
errors.append(f"{label} must contain valid JSON")
|
||||||
|
return None
|
||||||
|
if not isinstance(payload, dict):
|
||||||
|
errors.append(f"{label} must contain a JSON object")
|
||||||
|
return None
|
||||||
|
return payload
|
||||||
|
|
||||||
|
|
||||||
|
def reject_companion_unknown_fields(
|
||||||
|
payload: dict[str, Any],
|
||||||
|
allowed_keys: set[str],
|
||||||
|
prefix: str,
|
||||||
|
errors: list[str],
|
||||||
|
) -> None:
|
||||||
|
for key in sorted(set(payload) - allowed_keys):
|
||||||
|
errors.append(f"{prefix} field `{key}` is not accepted by plugin validation")
|
||||||
|
|
||||||
|
|
||||||
|
def validate_skill_manifests(plugin_root: Path, errors: list[str]) -> None:
|
||||||
|
skills_root = plugin_root / "skills"
|
||||||
|
if not skills_root.is_dir():
|
||||||
|
return
|
||||||
|
for skill_root in sorted(skills_root.iterdir(), key=lambda path: path.name):
|
||||||
|
if skill_root.name.startswith(".") or not skill_root.is_dir():
|
||||||
|
continue
|
||||||
|
validate_skill_manifest(skill_root, errors)
|
||||||
|
|
||||||
|
|
||||||
|
def validate_skill_manifest(skill_root: Path, errors: list[str]) -> None:
|
||||||
|
skill_md_path = skill_root / "SKILL.md"
|
||||||
|
if not skill_md_path.is_file():
|
||||||
|
errors.append(f"skill `{skill_root.name}` is missing `SKILL.md`")
|
||||||
|
return
|
||||||
|
try:
|
||||||
|
contents = skill_md_path.read_text(encoding="utf-8")
|
||||||
|
except OSError:
|
||||||
|
errors.append(f"unable to read skill `{skill_root.name}`")
|
||||||
|
return
|
||||||
|
if not contents.startswith("---\n"):
|
||||||
|
errors.append(f"skill `{skill_root.name}` must start with YAML frontmatter")
|
||||||
|
return
|
||||||
|
frontmatter_end = contents.find("\n---", 4)
|
||||||
|
if frontmatter_end == -1:
|
||||||
|
errors.append(f"skill `{skill_root.name}` frontmatter is not closed")
|
||||||
|
return
|
||||||
|
try:
|
||||||
|
frontmatter = yaml.safe_load(contents[4:frontmatter_end])
|
||||||
|
except yaml.YAMLError:
|
||||||
|
errors.append(f"skill `{skill_root.name}` frontmatter must be valid YAML")
|
||||||
|
return
|
||||||
|
if not isinstance(frontmatter, dict):
|
||||||
|
errors.append(f"skill `{skill_root.name}` frontmatter must be an object")
|
||||||
|
return
|
||||||
|
skill_name = frontmatter.get("name")
|
||||||
|
if not isinstance(skill_name, str) or not skill_name.strip():
|
||||||
|
errors.append(f"skill `{skill_root.name}` frontmatter field `name` must be non-empty")
|
||||||
|
description = frontmatter.get("description")
|
||||||
|
if not isinstance(description, str) or not description.strip():
|
||||||
|
errors.append(
|
||||||
|
f"skill `{skill_root.name}` frontmatter field `description` must be non-empty"
|
||||||
|
)
|
||||||
|
disable_model_invocation = frontmatter.get("disable-model-invocation")
|
||||||
|
if disable_model_invocation is None:
|
||||||
|
disable_model_invocation = frontmatter.get("disable_model_invocation")
|
||||||
|
if disable_model_invocation not in (None, False):
|
||||||
|
errors.append(
|
||||||
|
f"skill `{skill_root.name}` frontmatter field `disable-model-invocation` must be false"
|
||||||
|
)
|
||||||
|
agent_yaml_path = skill_root / "agents" / "openai.yaml"
|
||||||
|
if agent_yaml_path.is_file():
|
||||||
|
validate_skill_agent_manifest(
|
||||||
|
plugin_root=skill_root.parent.parent,
|
||||||
|
skill_root=skill_root,
|
||||||
|
agent_yaml_path=agent_yaml_path,
|
||||||
|
errors=errors,
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
def validate_skill_agent_manifest(
|
||||||
|
*,
|
||||||
|
plugin_root: Path,
|
||||||
|
skill_root: Path,
|
||||||
|
agent_yaml_path: Path,
|
||||||
|
errors: list[str],
|
||||||
|
) -> None:
|
||||||
|
try:
|
||||||
|
payload = yaml.safe_load(agent_yaml_path.read_text(encoding="utf-8"))
|
||||||
|
except OSError:
|
||||||
|
errors.append(f"unable to read skill `{skill_root.name}` agent YAML")
|
||||||
|
return
|
||||||
|
except yaml.YAMLError:
|
||||||
|
errors.append(f"skill `{skill_root.name}` agent YAML must be valid YAML")
|
||||||
|
return
|
||||||
|
if not isinstance(payload, dict):
|
||||||
|
errors.append(f"skill `{skill_root.name}` agent YAML must be an object")
|
||||||
|
return
|
||||||
|
|
||||||
|
reject_skill_agent_unknown_fields(
|
||||||
|
payload,
|
||||||
|
{"interface", "policy", "dependencies"},
|
||||||
|
skill_root,
|
||||||
|
errors,
|
||||||
|
)
|
||||||
|
interface = payload.get("interface")
|
||||||
|
if not isinstance(interface, dict):
|
||||||
|
errors.append(f"skill `{skill_root.name}` agent field `interface` must be an object")
|
||||||
|
return
|
||||||
|
reject_skill_agent_unknown_fields(
|
||||||
|
interface,
|
||||||
|
{
|
||||||
|
"display_name",
|
||||||
|
"short_description",
|
||||||
|
"icon_small",
|
||||||
|
"icon_large",
|
||||||
|
"brand_color",
|
||||||
|
"default_prompt",
|
||||||
|
},
|
||||||
|
skill_root,
|
||||||
|
errors,
|
||||||
|
prefix="interface",
|
||||||
|
)
|
||||||
|
for field in ("display_name", "short_description"):
|
||||||
|
value = interface.get(field)
|
||||||
|
if not isinstance(value, str) or not value.strip():
|
||||||
|
errors.append(
|
||||||
|
f"skill `{skill_root.name}` agent field `interface.{field}` must be non-empty"
|
||||||
|
)
|
||||||
|
for field in ("icon_small", "icon_large"):
|
||||||
|
validate_optional_asset_path(
|
||||||
|
skill_root,
|
||||||
|
plugin_root,
|
||||||
|
interface,
|
||||||
|
field,
|
||||||
|
errors,
|
||||||
|
prefix=f"skill `{skill_root.name}` agent field `interface",
|
||||||
|
)
|
||||||
|
brand_color = interface.get("brand_color")
|
||||||
|
if brand_color is not None and (
|
||||||
|
not isinstance(brand_color, str) or HEX_COLOR_RE.fullmatch(brand_color) is None
|
||||||
|
):
|
||||||
|
errors.append(
|
||||||
|
f"skill `{skill_root.name}` agent field `interface.brand_color` must use `#RRGGBB`"
|
||||||
|
)
|
||||||
|
default_prompt = interface.get("default_prompt")
|
||||||
|
if default_prompt is not None and (
|
||||||
|
not isinstance(default_prompt, str) or not default_prompt.strip()
|
||||||
|
):
|
||||||
|
errors.append(
|
||||||
|
f"skill `{skill_root.name}` agent field `interface.default_prompt` must be non-empty"
|
||||||
|
)
|
||||||
|
|
||||||
|
policy = payload.get("policy")
|
||||||
|
if policy is not None:
|
||||||
|
if not isinstance(policy, dict):
|
||||||
|
errors.append(f"skill `{skill_root.name}` agent field `policy` must be an object")
|
||||||
|
else:
|
||||||
|
reject_skill_agent_unknown_fields(
|
||||||
|
policy,
|
||||||
|
{"allow_implicit_invocation"},
|
||||||
|
skill_root,
|
||||||
|
errors,
|
||||||
|
prefix="policy",
|
||||||
|
)
|
||||||
|
allow_implicit_invocation = policy.get("allow_implicit_invocation")
|
||||||
|
if allow_implicit_invocation is not None and not isinstance(
|
||||||
|
allow_implicit_invocation,
|
||||||
|
bool,
|
||||||
|
):
|
||||||
|
errors.append(
|
||||||
|
f"skill `{skill_root.name}` agent field "
|
||||||
|
"`policy.allow_implicit_invocation` must be a boolean"
|
||||||
|
)
|
||||||
|
|
||||||
|
dependencies = payload.get("dependencies")
|
||||||
|
if dependencies is not None:
|
||||||
|
if not isinstance(dependencies, dict):
|
||||||
|
errors.append(
|
||||||
|
f"skill `{skill_root.name}` agent field `dependencies` must be an object"
|
||||||
|
)
|
||||||
|
else:
|
||||||
|
reject_skill_agent_unknown_fields(
|
||||||
|
dependencies,
|
||||||
|
{"tools"},
|
||||||
|
skill_root,
|
||||||
|
errors,
|
||||||
|
prefix="dependencies",
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
def reject_skill_agent_unknown_fields(
|
||||||
|
payload: dict[str, Any],
|
||||||
|
allowed_keys: set[str],
|
||||||
|
skill_root: Path,
|
||||||
|
errors: list[str],
|
||||||
|
*,
|
||||||
|
prefix: str | None = None,
|
||||||
|
) -> None:
|
||||||
|
for key in sorted(set(payload) - allowed_keys):
|
||||||
|
field = f"{prefix}.{key}" if prefix is not None else key
|
||||||
|
errors.append(
|
||||||
|
f"skill `{skill_root.name}` agent field `{field}` is not accepted by plugin validation"
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
def validate_optional_asset_path(
|
||||||
|
base_dir: Path,
|
||||||
|
allowed_root: Path,
|
||||||
|
payload: dict[str, Any],
|
||||||
|
key: str,
|
||||||
|
errors: list[str],
|
||||||
|
*,
|
||||||
|
prefix: str = "interface",
|
||||||
|
) -> None:
|
||||||
|
raw_path = payload.get(key)
|
||||||
|
if raw_path is None:
|
||||||
|
return
|
||||||
|
validate_asset_path(base_dir, allowed_root, raw_path, f"{prefix}.{key}", errors)
|
||||||
|
|
||||||
|
|
||||||
|
def validate_asset_path(
|
||||||
|
base_dir: Path,
|
||||||
|
allowed_root: Path,
|
||||||
|
raw_path: Any,
|
||||||
|
field: str,
|
||||||
|
errors: list[str],
|
||||||
|
) -> None:
|
||||||
|
label = field if field.startswith("skill `") else f"plugin.json field `{field}`"
|
||||||
|
if not isinstance(raw_path, str) or not raw_path.strip():
|
||||||
|
errors.append(f"{label} must be a non-empty relative path")
|
||||||
|
return
|
||||||
|
candidate = PurePosixPath(raw_path.replace("\\", "/"))
|
||||||
|
if candidate.is_absolute() or any(part in {"", ".", ".."} for part in candidate.parts):
|
||||||
|
errors.append(f"{label} must stay inside the plugin archive")
|
||||||
|
return
|
||||||
|
resolved_path = (base_dir / candidate.as_posix()).resolve()
|
||||||
|
if not resolved_path.is_relative_to(allowed_root.resolve()):
|
||||||
|
errors.append(f"{label} must stay inside the plugin archive")
|
||||||
|
return
|
||||||
|
if not resolved_path.is_file():
|
||||||
|
errors.append(f"{label} points to a missing file")
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
main()
|
||||||
57
skills/.system/review-agent/SKILL.md
Normal file
57
skills/.system/review-agent/SKILL.md
Normal file
@ -0,0 +1,57 @@
|
|||||||
|
---
|
||||||
|
name: review-agent
|
||||||
|
description: Perform a read-only, defect-first review of a specified code change and return every actionable finding. Use when another agent delegates review of uncommitted changes, a base-branch diff, a commit, or custom review instructions.
|
||||||
|
---
|
||||||
|
|
||||||
|
# Review Agent
|
||||||
|
|
||||||
|
Inspect the requested target directly and return every finding that the author would likely fix.
|
||||||
|
Do not modify files, create commits, push branches, post review comments, or delegate the review
|
||||||
|
to another agent.
|
||||||
|
|
||||||
|
## Review the change
|
||||||
|
|
||||||
|
1. Read the applicable `AGENTS.md` instructions.
|
||||||
|
2. Inspect the complete diff for the requested target and enough surrounding code to understand
|
||||||
|
each changed path.
|
||||||
|
3. Identify concrete regressions introduced by the change. Continue through the whole diff after
|
||||||
|
finding the first issue.
|
||||||
|
4. Check the relevant tests and call sites to confirm that each finding is real and actionable.
|
||||||
|
|
||||||
|
For a base-branch review, compare the changes that would actually merge rather than diffing
|
||||||
|
directly against the branch tip. Resolve the comparison ref to the branch's upstream when that
|
||||||
|
upstream exists and is ahead of the local branch; otherwise use the local branch. Run
|
||||||
|
`git merge-base HEAD <comparison-ref>`, then inspect `git diff <merge-base-sha>`. If the local
|
||||||
|
branch cannot be resolved, try its configured upstream explicitly before reporting that the target
|
||||||
|
is unavailable.
|
||||||
|
|
||||||
|
Flag an issue only when all of these are true:
|
||||||
|
|
||||||
|
- It affects correctness, security, performance, or maintainability in a meaningful way.
|
||||||
|
- It is discrete and actionable.
|
||||||
|
- It was introduced by the reviewed change.
|
||||||
|
- The affected scenario or call path can be demonstrated from the code.
|
||||||
|
- The author would probably fix it if they knew about it.
|
||||||
|
|
||||||
|
Do not flag speculative concerns, pre-existing problems, intentional behavior changes, or style
|
||||||
|
nits that do not obscure the code.
|
||||||
|
|
||||||
|
## Write the result
|
||||||
|
|
||||||
|
Present findings first, ordered by severity. Use one entry per issue in this form:
|
||||||
|
|
||||||
|
`[P1] Imperative finding title — path/to/file.rs:line`
|
||||||
|
|
||||||
|
Follow the title with one short paragraph explaining the affected scenario and why the behavior is
|
||||||
|
wrong. Keep the cited range as small as possible and make sure it overlaps the reviewed diff.
|
||||||
|
|
||||||
|
Use these priorities:
|
||||||
|
|
||||||
|
- `P0`: universal release blocker or critical failure.
|
||||||
|
- `P1`: urgent defect that should be fixed next.
|
||||||
|
- `P2`: ordinary defect that should be fixed.
|
||||||
|
- `P3`: low-impact issue that is still worth fixing.
|
||||||
|
|
||||||
|
If there are no qualifying findings, say `No findings.` Do not invent a finding to fill the result.
|
||||||
|
After the findings, add a brief overall assessment and mention any material test gaps or residual
|
||||||
|
risks.
|
||||||
6
skills/.system/review-agent/agents/openai.yaml
Normal file
6
skills/.system/review-agent/agents/openai.yaml
Normal file
@ -0,0 +1,6 @@
|
|||||||
|
interface:
|
||||||
|
display_name: "Review Agent"
|
||||||
|
short_description: "Find actionable bugs in code changes"
|
||||||
|
default_prompt: "Use $review-agent to review the requested code changes and return actionable findings."
|
||||||
|
policy:
|
||||||
|
allow_implicit_invocation: false
|
||||||
416
skills/.system/skill-creator/SKILL.md
Normal file
416
skills/.system/skill-creator/SKILL.md
Normal file
@ -0,0 +1,416 @@
|
|||||||
|
---
|
||||||
|
name: skill-creator
|
||||||
|
description: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations.
|
||||||
|
metadata:
|
||||||
|
short-description: Create or update a skill
|
||||||
|
---
|
||||||
|
|
||||||
|
# Skill Creator
|
||||||
|
|
||||||
|
This skill provides guidance for creating effective skills.
|
||||||
|
|
||||||
|
## About Skills
|
||||||
|
|
||||||
|
Skills are modular, self-contained folders that extend Codex's capabilities by providing
|
||||||
|
specialized knowledge, workflows, and tools. Think of them as "onboarding guides" for specific
|
||||||
|
domains or tasks—they transform Codex from a general-purpose agent into a specialized agent
|
||||||
|
equipped with procedural knowledge that no model can fully possess.
|
||||||
|
|
||||||
|
### What Skills Provide
|
||||||
|
|
||||||
|
1. Specialized workflows - Multi-step procedures for specific domains
|
||||||
|
2. Tool integrations - Instructions for working with specific file formats or APIs
|
||||||
|
3. Domain expertise - Company-specific knowledge, schemas, business logic
|
||||||
|
4. Bundled resources - Scripts, references, and assets for complex and repetitive tasks
|
||||||
|
|
||||||
|
## Core Principles
|
||||||
|
|
||||||
|
### Concise is Key
|
||||||
|
|
||||||
|
The context window is a public good. Skills share the context window with everything else Codex needs: system prompt, conversation history, other Skills' metadata, and the actual user request.
|
||||||
|
|
||||||
|
**Default assumption: Codex is already very smart.** Only add context Codex doesn't already have. Challenge each piece of information: "Does Codex really need this explanation?" and "Does this paragraph justify its token cost?"
|
||||||
|
|
||||||
|
Prefer concise examples over verbose explanations.
|
||||||
|
|
||||||
|
### Set Appropriate Degrees of Freedom
|
||||||
|
|
||||||
|
Match the level of specificity to the task's fragility and variability:
|
||||||
|
|
||||||
|
**High freedom (text-based instructions)**: Use when multiple approaches are valid, decisions depend on context, or heuristics guide the approach.
|
||||||
|
|
||||||
|
**Medium freedom (pseudocode or scripts with parameters)**: Use when a preferred pattern exists, some variation is acceptable, or configuration affects behavior.
|
||||||
|
|
||||||
|
**Low freedom (specific scripts, few parameters)**: Use when operations are fragile and error-prone, consistency is critical, or a specific sequence must be followed.
|
||||||
|
|
||||||
|
Think of Codex as exploring a path: a narrow bridge with cliffs needs specific guardrails (low freedom), while an open field allows many routes (high freedom).
|
||||||
|
|
||||||
|
### Protect Validation Integrity
|
||||||
|
|
||||||
|
You may use subagents during iteration to validate whether a skill works on realistic tasks or whether a suspected problem is real. This is most useful when you want an independent pass on the skill's behavior, outputs, or failure modes after a revision. Only do this when it is possible to start new subagents.
|
||||||
|
|
||||||
|
When using subagents for validation, treat that as an evaluation surface. The goal is to learn whether the skill generalizes, not whether another agent can reconstruct the answer from leaked context.
|
||||||
|
|
||||||
|
Prefer raw artifacts such as example prompts, outputs, diffs, logs, or traces. Give the minimum task-local context needed to perform the validation. Avoid passing the intended answer, suspected bug, intended fix, or your prior conclusions unless the validation explicitly requires them.
|
||||||
|
|
||||||
|
### Anatomy of a Skill
|
||||||
|
|
||||||
|
Every skill consists of a required SKILL.md file and optional bundled resources:
|
||||||
|
|
||||||
|
```
|
||||||
|
skill-name/
|
||||||
|
├── SKILL.md (required)
|
||||||
|
│ ├── YAML frontmatter metadata (required)
|
||||||
|
│ │ ├── name: (required)
|
||||||
|
│ │ └── description: (required)
|
||||||
|
│ └── Markdown instructions (required)
|
||||||
|
├── agents/ (recommended)
|
||||||
|
│ └── openai.yaml - UI metadata for skill lists and chips
|
||||||
|
└── Bundled Resources (optional)
|
||||||
|
├── scripts/ - Executable code (Python/Bash/etc.)
|
||||||
|
├── references/ - Documentation intended to be loaded into context as needed
|
||||||
|
└── assets/ - Files used in output (templates, icons, fonts, etc.)
|
||||||
|
```
|
||||||
|
|
||||||
|
#### SKILL.md (required)
|
||||||
|
|
||||||
|
Every SKILL.md consists of:
|
||||||
|
|
||||||
|
- **Frontmatter** (YAML): Contains `name` and `description` fields. These are the only fields that Codex reads to determine when the skill gets used, thus it is very important to be clear and comprehensive in describing what the skill is, and when it should be used.
|
||||||
|
- **Body** (Markdown): Instructions and guidance for using the skill. Only loaded AFTER the skill triggers (if at all).
|
||||||
|
|
||||||
|
#### Agents metadata (recommended)
|
||||||
|
|
||||||
|
- UI-facing metadata for skill lists and chips
|
||||||
|
- Read references/openai_yaml.md before generating values and follow its descriptions and constraints
|
||||||
|
- Create: human-facing `display_name`, `short_description`, and `default_prompt` by reading the skill
|
||||||
|
- Generate deterministically by passing the values as `--interface key=value` to `scripts/generate_openai_yaml.py` or `scripts/init_skill.py`
|
||||||
|
- On updates: validate `agents/openai.yaml` still matches SKILL.md; regenerate if stale
|
||||||
|
- Only include other optional interface fields (icons, brand color) if explicitly provided
|
||||||
|
- See references/openai_yaml.md for field definitions and examples
|
||||||
|
|
||||||
|
#### Bundled Resources (optional)
|
||||||
|
|
||||||
|
##### Scripts (`scripts/`)
|
||||||
|
|
||||||
|
Executable code (Python/Bash/etc.) for tasks that require deterministic reliability or are repeatedly rewritten.
|
||||||
|
|
||||||
|
- **When to include**: When the same code is being rewritten repeatedly or deterministic reliability is needed
|
||||||
|
- **Example**: `scripts/rotate_pdf.py` for PDF rotation tasks
|
||||||
|
- **Benefits**: Token efficient, deterministic, may be executed without loading into context
|
||||||
|
- **Note**: Scripts may still need to be read by Codex for patching or environment-specific adjustments
|
||||||
|
|
||||||
|
##### References (`references/`)
|
||||||
|
|
||||||
|
Documentation and reference material intended to be loaded as needed into context to inform Codex's process and thinking.
|
||||||
|
|
||||||
|
- **When to include**: For documentation that Codex should reference while working
|
||||||
|
- **Examples**: `references/finance.md` for financial schemas, `references/mnda.md` for company NDA template, `references/policies.md` for company policies, `references/api_docs.md` for API specifications
|
||||||
|
- **Use cases**: Database schemas, API documentation, domain knowledge, company policies, detailed workflow guides
|
||||||
|
- **Benefits**: Keeps SKILL.md lean, loaded only when Codex determines it's needed
|
||||||
|
- **Best practice**: If files are large (>10k words), include grep search patterns in SKILL.md
|
||||||
|
- **Avoid duplication**: Information should live in either SKILL.md or references files, not both. Prefer references files for detailed information unless it's truly core to the skill—this keeps SKILL.md lean while making information discoverable without hogging the context window. Keep only essential procedural instructions and workflow guidance in SKILL.md; move detailed reference material, schemas, and examples to references files.
|
||||||
|
|
||||||
|
##### Assets (`assets/`)
|
||||||
|
|
||||||
|
Files not intended to be loaded into context, but rather used within the output Codex produces.
|
||||||
|
|
||||||
|
- **When to include**: When the skill needs files that will be used in the final output
|
||||||
|
- **Examples**: `assets/logo.png` for brand assets, `assets/slides.pptx` for PowerPoint templates, `assets/frontend-template/` for HTML/React boilerplate, `assets/font.ttf` for typography
|
||||||
|
- **Use cases**: Templates, images, icons, boilerplate code, fonts, sample documents that get copied or modified
|
||||||
|
- **Benefits**: Separates output resources from documentation, enables Codex to use files without loading them into context
|
||||||
|
|
||||||
|
#### What to Not Include in a Skill
|
||||||
|
|
||||||
|
A skill should only contain essential files that directly support its functionality. Do NOT create extraneous documentation or auxiliary files, including:
|
||||||
|
|
||||||
|
- README.md
|
||||||
|
- INSTALLATION_GUIDE.md
|
||||||
|
- QUICK_REFERENCE.md
|
||||||
|
- CHANGELOG.md
|
||||||
|
- etc.
|
||||||
|
|
||||||
|
The skill should only contain the information needed for an AI agent to do the job at hand. It should not contain auxiliary context about the process that went into creating it, setup and testing procedures, user-facing documentation, etc. Creating additional documentation files just adds clutter and confusion.
|
||||||
|
|
||||||
|
### Progressive Disclosure Design Principle
|
||||||
|
|
||||||
|
Skills use a three-level loading system to manage context efficiently:
|
||||||
|
|
||||||
|
1. **Metadata (name + description)** - Always in context (~100 words)
|
||||||
|
2. **SKILL.md body** - When skill triggers (<5k words)
|
||||||
|
3. **Bundled resources** - As needed by Codex (Unlimited because scripts can be executed without reading into context window)
|
||||||
|
|
||||||
|
#### Progressive Disclosure Patterns
|
||||||
|
|
||||||
|
Keep SKILL.md body to the essentials and under 500 lines to minimize context bloat. Split content into separate files when approaching this limit. When splitting out content into other files, it is very important to reference them from SKILL.md and describe clearly when to read them, to ensure the reader of the skill knows they exist and when to use them.
|
||||||
|
|
||||||
|
**Key principle:** When a skill supports multiple variations, frameworks, or options, keep only the core workflow and selection guidance in SKILL.md. Move variant-specific details (patterns, examples, configuration) into separate reference files.
|
||||||
|
|
||||||
|
**Pattern 1: High-level guide with references**
|
||||||
|
|
||||||
|
```markdown
|
||||||
|
# PDF Processing
|
||||||
|
|
||||||
|
## Quick start
|
||||||
|
|
||||||
|
Extract text with pdfplumber:
|
||||||
|
[code example]
|
||||||
|
|
||||||
|
## Advanced features
|
||||||
|
|
||||||
|
- **Form filling**: See [FORMS.md](FORMS.md) for complete guide
|
||||||
|
- **API reference**: See [REFERENCE.md](REFERENCE.md) for all methods
|
||||||
|
- **Examples**: See [EXAMPLES.md](EXAMPLES.md) for common patterns
|
||||||
|
```
|
||||||
|
|
||||||
|
Codex loads FORMS.md, REFERENCE.md, or EXAMPLES.md only when needed.
|
||||||
|
|
||||||
|
**Pattern 2: Domain-specific organization**
|
||||||
|
|
||||||
|
For Skills with multiple domains, organize content by domain to avoid loading irrelevant context:
|
||||||
|
|
||||||
|
```
|
||||||
|
bigquery-skill/
|
||||||
|
├── SKILL.md (overview and navigation)
|
||||||
|
└── reference/
|
||||||
|
├── finance.md (revenue, billing metrics)
|
||||||
|
├── sales.md (opportunities, pipeline)
|
||||||
|
├── product.md (API usage, features)
|
||||||
|
└── marketing.md (campaigns, attribution)
|
||||||
|
```
|
||||||
|
|
||||||
|
When a user asks about sales metrics, Codex only reads sales.md.
|
||||||
|
|
||||||
|
Similarly, for skills supporting multiple frameworks or variants, organize by variant:
|
||||||
|
|
||||||
|
```
|
||||||
|
cloud-deploy/
|
||||||
|
├── SKILL.md (workflow + provider selection)
|
||||||
|
└── references/
|
||||||
|
├── aws.md (AWS deployment patterns)
|
||||||
|
├── gcp.md (GCP deployment patterns)
|
||||||
|
└── azure.md (Azure deployment patterns)
|
||||||
|
```
|
||||||
|
|
||||||
|
When the user chooses AWS, Codex only reads aws.md.
|
||||||
|
|
||||||
|
**Pattern 3: Conditional details**
|
||||||
|
|
||||||
|
Show basic content, link to advanced content:
|
||||||
|
|
||||||
|
```markdown
|
||||||
|
# DOCX Processing
|
||||||
|
|
||||||
|
## Creating documents
|
||||||
|
|
||||||
|
Use docx-js for new documents. See [DOCX-JS.md](DOCX-JS.md).
|
||||||
|
|
||||||
|
## Editing documents
|
||||||
|
|
||||||
|
For simple edits, modify the XML directly.
|
||||||
|
|
||||||
|
**For tracked changes**: See [REDLINING.md](REDLINING.md)
|
||||||
|
**For OOXML details**: See [OOXML.md](OOXML.md)
|
||||||
|
```
|
||||||
|
|
||||||
|
Codex reads REDLINING.md or OOXML.md only when the user needs those features.
|
||||||
|
|
||||||
|
**Important guidelines:**
|
||||||
|
|
||||||
|
- **Avoid deeply nested references** - Keep references one level deep from SKILL.md. All reference files should link directly from SKILL.md.
|
||||||
|
- **Structure longer reference files** - For files longer than 100 lines, include a table of contents at the top so Codex can see the full scope when previewing.
|
||||||
|
|
||||||
|
## Skill Creation Process
|
||||||
|
|
||||||
|
Skill creation involves these steps:
|
||||||
|
|
||||||
|
1. Understand the skill with concrete examples
|
||||||
|
2. Plan reusable skill contents (scripts, references, assets)
|
||||||
|
3. Initialize the skill (run init_skill.py)
|
||||||
|
4. Edit the skill (implement resources and write SKILL.md)
|
||||||
|
5. Validate the skill (run quick_validate.py)
|
||||||
|
6. Iterate based on real usage and forward-test complex skills.
|
||||||
|
|
||||||
|
Follow these steps in order, skipping only if there is a clear reason why they are not applicable.
|
||||||
|
|
||||||
|
### Skill Naming
|
||||||
|
|
||||||
|
- Use lowercase letters, digits, and hyphens only; normalize user-provided titles to hyphen-case (e.g., "Plan Mode" -> `plan-mode`).
|
||||||
|
- When generating names, generate a name under 64 characters (letters, digits, hyphens).
|
||||||
|
- Prefer short, verb-led phrases that describe the action.
|
||||||
|
- Namespace by tool when it improves clarity or triggering (e.g., `gh-address-comments`, `linear-address-issue`).
|
||||||
|
- Name the skill folder exactly after the skill name.
|
||||||
|
|
||||||
|
### Step 1: Understanding the Skill with Concrete Examples
|
||||||
|
|
||||||
|
Skip this step only when the skill's usage patterns are already clearly understood. It remains valuable even when working with an existing skill.
|
||||||
|
|
||||||
|
To create an effective skill, clearly understand concrete examples of how the skill will be used. This understanding can come from either direct user examples or generated examples that are validated with user feedback.
|
||||||
|
|
||||||
|
For example, when building an image-editor skill, relevant questions include:
|
||||||
|
|
||||||
|
- "What functionality should the image-editor skill support? Editing, rotating, anything else?"
|
||||||
|
- "Can you give some examples of how this skill would be used?"
|
||||||
|
- "I can imagine users asking for things like 'Remove the red-eye from this image' or 'Rotate this image'. Are there other ways you imagine this skill being used?"
|
||||||
|
- "What would a user say that should trigger this skill?"
|
||||||
|
- "Where should I create this skill? If you do not have a preference, I will place it in `$CODEX_HOME/skills` (or `~/.codex/skills` when `CODEX_HOME` is unset) so Codex can discover it automatically."
|
||||||
|
|
||||||
|
To avoid overwhelming users, avoid asking too many questions in a single message. Start with the most important questions and follow up as needed for better effectiveness.
|
||||||
|
|
||||||
|
Conclude this step when there is a clear sense of the functionality the skill should support.
|
||||||
|
|
||||||
|
### Step 2: Planning the Reusable Skill Contents
|
||||||
|
|
||||||
|
To turn concrete examples into an effective skill, analyze each example by:
|
||||||
|
|
||||||
|
1. Considering how to execute on the example from scratch
|
||||||
|
2. Identifying what scripts, references, and assets would be helpful when executing these workflows repeatedly
|
||||||
|
|
||||||
|
Example: When building a `pdf-editor` skill to handle queries like "Help me rotate this PDF," the analysis shows:
|
||||||
|
|
||||||
|
1. Rotating a PDF requires re-writing the same code each time
|
||||||
|
2. A `scripts/rotate_pdf.py` script would be helpful to store in the skill
|
||||||
|
|
||||||
|
Example: When designing a `frontend-webapp-builder` skill for queries like "Build me a todo app" or "Build me a dashboard to track my steps," the analysis shows:
|
||||||
|
|
||||||
|
1. Writing a frontend webapp requires the same boilerplate HTML/React each time
|
||||||
|
2. An `assets/hello-world/` template containing the boilerplate HTML/React project files would be helpful to store in the skill
|
||||||
|
|
||||||
|
Example: When building a `big-query` skill to handle queries like "How many users have logged in today?" the analysis shows:
|
||||||
|
|
||||||
|
1. Querying BigQuery requires re-discovering the table schemas and relationships each time
|
||||||
|
2. A `references/schema.md` file documenting the table schemas would be helpful to store in the skill
|
||||||
|
|
||||||
|
To establish the skill's contents, analyze each concrete example to create a list of the reusable resources to include: scripts, references, and assets.
|
||||||
|
|
||||||
|
### Step 3: Initializing the Skill
|
||||||
|
|
||||||
|
At this point, it is time to actually create the skill.
|
||||||
|
|
||||||
|
Skip this step only if the skill being developed already exists. In this case, continue to the next step.
|
||||||
|
|
||||||
|
Before running `init_skill.py`, ask where the user wants the skill created. If they do not specify a location, default to `$CODEX_HOME/skills`; when `CODEX_HOME` is unset, fall back to `~/.codex/skills` so the skill is auto-discovered.
|
||||||
|
|
||||||
|
When creating a new skill from scratch, always run the `init_skill.py` script. The script conveniently generates a new template skill directory that automatically includes everything a skill requires, making the skill creation process much more efficient and reliable.
|
||||||
|
|
||||||
|
Usage:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
scripts/init_skill.py <skill-name> --path <output-directory> [--resources scripts,references,assets] [--examples]
|
||||||
|
```
|
||||||
|
|
||||||
|
Examples:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
scripts/init_skill.py my-skill --path "${CODEX_HOME:-$HOME/.codex}/skills"
|
||||||
|
scripts/init_skill.py my-skill --path "${CODEX_HOME:-$HOME/.codex}/skills" --resources scripts,references
|
||||||
|
scripts/init_skill.py my-skill --path ~/work/skills --resources scripts --examples
|
||||||
|
```
|
||||||
|
|
||||||
|
The script:
|
||||||
|
|
||||||
|
- Creates the skill directory at the specified path
|
||||||
|
- Generates a SKILL.md template with proper frontmatter and TODO placeholders
|
||||||
|
- Creates `agents/openai.yaml` using agent-generated `display_name`, `short_description`, and `default_prompt` passed via `--interface key=value`
|
||||||
|
- Optionally creates resource directories based on `--resources`
|
||||||
|
- Optionally adds example files when `--examples` is set
|
||||||
|
|
||||||
|
After initialization, customize the SKILL.md and add resources as needed. If you used `--examples`, replace or delete placeholder files.
|
||||||
|
|
||||||
|
Generate `display_name`, `short_description`, and `default_prompt` by reading the skill, then pass them as `--interface key=value` to `init_skill.py` or regenerate with:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
scripts/generate_openai_yaml.py <path/to/skill-folder> --interface key=value
|
||||||
|
```
|
||||||
|
|
||||||
|
Only include other optional interface fields when the user explicitly provides them. For full field descriptions and examples, see references/openai_yaml.md.
|
||||||
|
|
||||||
|
### Step 4: Edit the Skill
|
||||||
|
|
||||||
|
When editing the (newly-generated or existing) skill, remember that the skill is being created for another instance of Codex to use. Include information that would be beneficial and non-obvious to Codex. Consider what procedural knowledge, domain-specific details, or reusable assets would help another Codex instance execute these tasks more effectively.
|
||||||
|
|
||||||
|
After substantial revisions, or if the skill is particularly tricky, you should use subagents to forward-test the skill on realistic tasks or artifacts. When doing so, pass the artifact under validation rather than your diagnosis of what is wrong, and keep the prompt generic enough that success depends on transferable reasoning rather than hidden ground truth.
|
||||||
|
|
||||||
|
#### Start with Reusable Skill Contents
|
||||||
|
|
||||||
|
To begin implementation, start with the reusable resources identified above: `scripts/`, `references/`, and `assets/` files. Note that this step may require user input. For example, when implementing a `brand-guidelines` skill, the user may need to provide brand assets or templates to store in `assets/`, or documentation to store in `references/`.
|
||||||
|
|
||||||
|
Added scripts must be tested by actually running them to ensure there are no bugs and that the output matches what is expected. If there are many similar scripts, only a representative sample needs to be tested to ensure confidence that they all work while balancing time to completion.
|
||||||
|
|
||||||
|
If you used `--examples`, delete any placeholder files that are not needed for the skill. Only create resource directories that are actually required.
|
||||||
|
|
||||||
|
#### Update SKILL.md
|
||||||
|
|
||||||
|
**Writing Guidelines:** Always use imperative/infinitive form.
|
||||||
|
|
||||||
|
##### Frontmatter
|
||||||
|
|
||||||
|
Write the YAML frontmatter with `name` and `description`:
|
||||||
|
|
||||||
|
- `name`: The skill name
|
||||||
|
- `description`: This is the primary triggering mechanism for your skill, and helps Codex understand when to use the skill.
|
||||||
|
- Include both what the Skill does and specific triggers/contexts for when to use it.
|
||||||
|
- Include all "when to use" information here - Not in the body. The body is only loaded after triggering, so "When to Use This Skill" sections in the body are not helpful to Codex.
|
||||||
|
- Example description for a `docx` skill: "Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. Use when Codex needs to work with professional documents (.docx files) for: (1) Creating new documents, (2) Modifying or editing content, (3) Working with tracked changes, (4) Adding comments, or any other document tasks"
|
||||||
|
|
||||||
|
Do not include any other fields in YAML frontmatter.
|
||||||
|
|
||||||
|
##### Body
|
||||||
|
|
||||||
|
Write instructions for using the skill and its bundled resources.
|
||||||
|
|
||||||
|
### Step 5: Validate the Skill
|
||||||
|
|
||||||
|
Once development of the skill is complete, validate the skill folder to catch basic issues early:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
scripts/quick_validate.py <path/to/skill-folder>
|
||||||
|
```
|
||||||
|
|
||||||
|
The validation script checks YAML frontmatter format, required fields, and naming rules. If validation fails, fix the reported issues and run the command again.
|
||||||
|
|
||||||
|
### Step 6: Iterate
|
||||||
|
|
||||||
|
After testing the skill, you may detect the skill is complex enough that it requires forward-testing; or users may request improvements.
|
||||||
|
|
||||||
|
User testing often this happens right after using the skill, with fresh context of how the skill performed.
|
||||||
|
|
||||||
|
**Forward-testing and iteration workflow:**
|
||||||
|
|
||||||
|
1. Use the skill on real tasks
|
||||||
|
2. Notice struggles or inefficiencies
|
||||||
|
3. Identify how SKILL.md or bundled resources should be updated
|
||||||
|
4. Implement changes and test again
|
||||||
|
5. Forward-test if it is reasonable and appropriate
|
||||||
|
|
||||||
|
## Forward-testing
|
||||||
|
|
||||||
|
To forward-test, launch subagents as a way to stress test the skill with minimal context.
|
||||||
|
Subagents should *not* know that they are being asked to test the skill. They should be treated as
|
||||||
|
an agent asked to perform a task by the user. Prompts to subagents should look like:
|
||||||
|
`Use $skill-x at /path/to/skill-x to solve problem y`
|
||||||
|
Not:
|
||||||
|
`Review the skill at /path/to/skill-x; pretend a user asks you to...`
|
||||||
|
|
||||||
|
Decision rule for forward-testing:
|
||||||
|
- Err on the side of forward-testing
|
||||||
|
- Ask for approval if you think there's a risk that forward-testing would:
|
||||||
|
* take a long time,
|
||||||
|
* require additional approvals from the user, or
|
||||||
|
* modify live production systems
|
||||||
|
|
||||||
|
In these cases, show the user your proposed prompt and request (1) a yes/no decision, and
|
||||||
|
(2) any suggested modifictions.
|
||||||
|
|
||||||
|
Considerations when forward-testing:
|
||||||
|
- use fresh threads for independent passes
|
||||||
|
- pass the skill, and a request in a similar way the user would.
|
||||||
|
- pass raw artifacts, not your conclusions
|
||||||
|
- avoid showing expected answers or intended fixes
|
||||||
|
- rebuild context from source artifacts after each iteration
|
||||||
|
- review the subagent's output and reasoning and emitted artifacts
|
||||||
|
- avoid leaving artifacts the agent can find on disk between iterations;
|
||||||
|
clean up subagents' artifacts to avoid additional contamination.
|
||||||
|
|
||||||
|
If forward-testing only succeeds when subagents see leaked context, tighten the skill or the
|
||||||
|
forward-testing setup before trusting the result.
|
||||||
5
skills/.system/skill-creator/agents/openai.yaml
Normal file
5
skills/.system/skill-creator/agents/openai.yaml
Normal file
@ -0,0 +1,5 @@
|
|||||||
|
interface:
|
||||||
|
display_name: "Skill Creator"
|
||||||
|
short_description: "Create or update a skill"
|
||||||
|
icon_small: "./assets/skill-creator-small.svg"
|
||||||
|
icon_large: "./assets/skill-creator.png"
|
||||||
@ -0,0 +1,3 @@
|
|||||||
|
<svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" fill="currentColor" viewBox="0 0 20 20">
|
||||||
|
<path fill="#0D0D0D" d="M12.03 4.113a3.612 3.612 0 0 1 5.108 5.108l-6.292 6.29c-.324.324-.56.561-.791.752l-.235.176c-.205.14-.422.261-.65.36l-.229.093a4.136 4.136 0 0 1-.586.16l-.764.134-2.394.4c-.142.024-.294.05-.423.06-.098.007-.232.01-.378-.026l-.149-.05a1.081 1.081 0 0 1-.521-.474l-.046-.093a1.104 1.104 0 0 1-.075-.527c.01-.129.035-.28.06-.422l.398-2.394c.1-.602.162-.987.295-1.35l.093-.23c.1-.228.22-.445.36-.65l.176-.235c.19-.232.428-.467.751-.79l6.292-6.292Zm-5.35 7.232c-.35.35-.534.535-.66.688l-.11.147a2.67 2.67 0 0 0-.24.433l-.062.154c-.08.22-.124.462-.232 1.112l-.398 2.394-.001.001h.003l2.393-.399.717-.126a2.63 2.63 0 0 0 .394-.105l.154-.063a2.65 2.65 0 0 0 .433-.24l.147-.11c.153-.126.339-.31.688-.66l4.988-4.988-3.227-3.226-4.987 4.988Zm9.517-6.291a2.281 2.281 0 0 0-3.225 0l-.364.362 3.226 3.227.363-.364c.89-.89.89-2.334 0-3.225ZM4.583 1.783a.3.3 0 0 1 .294.241c.117.585.347 1.092.707 1.48.357.385.859.668 1.549.783a.3.3 0 0 1 0 .592c-.69.115-1.192.398-1.549.783-.315.34-.53.77-.657 1.265l-.05.215a.3.3 0 0 1-.588 0c-.117-.585-.347-1.092-.707-1.48-.357-.384-.859-.668-1.549-.783a.3.3 0 0 1 0-.592c.69-.115 1.192-.398 1.549-.783.36-.388.59-.895.707-1.48l.015-.05a.3.3 0 0 1 .279-.19Z"/>
|
||||||
|
</svg>
|
||||||
|
After Width: | Height: | Size: 1.3 KiB |
BIN
skills/.system/skill-creator/assets/skill-creator.png
Normal file
BIN
skills/.system/skill-creator/assets/skill-creator.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 1.5 KiB |
202
skills/.system/skill-creator/license.txt
Normal file
202
skills/.system/skill-creator/license.txt
Normal file
@ -0,0 +1,202 @@
|
|||||||
|
|
||||||
|
Apache License
|
||||||
|
Version 2.0, January 2004
|
||||||
|
http://www.apache.org/licenses/
|
||||||
|
|
||||||
|
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
|
||||||
|
|
||||||
|
1. Definitions.
|
||||||
|
|
||||||
|
"License" shall mean the terms and conditions for use, reproduction,
|
||||||
|
and distribution as defined by Sections 1 through 9 of this document.
|
||||||
|
|
||||||
|
"Licensor" shall mean the copyright owner or entity authorized by
|
||||||
|
the copyright owner that is granting the License.
|
||||||
|
|
||||||
|
"Legal Entity" shall mean the union of the acting entity and all
|
||||||
|
other entities that control, are controlled by, or are under common
|
||||||
|
control with that entity. For the purposes of this definition,
|
||||||
|
"control" means (i) the power, direct or indirect, to cause the
|
||||||
|
direction or management of such entity, whether by contract or
|
||||||
|
otherwise, or (ii) ownership of fifty percent (50%) or more of the
|
||||||
|
outstanding shares, or (iii) beneficial ownership of such entity.
|
||||||
|
|
||||||
|
"You" (or "Your") shall mean an individual or Legal Entity
|
||||||
|
exercising permissions granted by this License.
|
||||||
|
|
||||||
|
"Source" form shall mean the preferred form for making modifications,
|
||||||
|
including but not limited to software source code, documentation
|
||||||
|
source, and configuration files.
|
||||||
|
|
||||||
|
"Object" form shall mean any form resulting from mechanical
|
||||||
|
transformation or translation of a Source form, including but
|
||||||
|
not limited to compiled object code, generated documentation,
|
||||||
|
and conversions to other media types.
|
||||||
|
|
||||||
|
"Work" shall mean the work of authorship, whether in Source or
|
||||||
|
Object form, made available under the License, as indicated by a
|
||||||
|
copyright notice that is included in or attached to the work
|
||||||
|
(an example is provided in the Appendix below).
|
||||||
|
|
||||||
|
"Derivative Works" shall mean any work, whether in Source or Object
|
||||||
|
form, that is based on (or derived from) the Work and for which the
|
||||||
|
editorial revisions, annotations, elaborations, or other modifications
|
||||||
|
represent, as a whole, an original work of authorship. For the purposes
|
||||||
|
of this License, Derivative Works shall not include works that remain
|
||||||
|
separable from, or merely link (or bind by name) to the interfaces of,
|
||||||
|
the Work and Derivative Works thereof.
|
||||||
|
|
||||||
|
"Contribution" shall mean any work of authorship, including
|
||||||
|
the original version of the Work and any modifications or additions
|
||||||
|
to that Work or Derivative Works thereof, that is intentionally
|
||||||
|
submitted to Licensor for inclusion in the Work by the copyright owner
|
||||||
|
or by an individual or Legal Entity authorized to submit on behalf of
|
||||||
|
the copyright owner. For the purposes of this definition, "submitted"
|
||||||
|
means any form of electronic, verbal, or written communication sent
|
||||||
|
to the Licensor or its representatives, including but not limited to
|
||||||
|
communication on electronic mailing lists, source code control systems,
|
||||||
|
and issue tracking systems that are managed by, or on behalf of, the
|
||||||
|
Licensor for the purpose of discussing and improving the Work, but
|
||||||
|
excluding communication that is conspicuously marked or otherwise
|
||||||
|
designated in writing by the copyright owner as "Not a Contribution."
|
||||||
|
|
||||||
|
"Contributor" shall mean Licensor and any individual or Legal Entity
|
||||||
|
on behalf of whom a Contribution has been received by Licensor and
|
||||||
|
subsequently incorporated within the Work.
|
||||||
|
|
||||||
|
2. Grant of Copyright License. Subject to the terms and conditions of
|
||||||
|
this License, each Contributor hereby grants to You a perpetual,
|
||||||
|
worldwide, non-exclusive, no-charge, royalty-free, irrevocable
|
||||||
|
copyright license to reproduce, prepare Derivative Works of,
|
||||||
|
publicly display, publicly perform, sublicense, and distribute the
|
||||||
|
Work and such Derivative Works in Source or Object form.
|
||||||
|
|
||||||
|
3. Grant of Patent License. Subject to the terms and conditions of
|
||||||
|
this License, each Contributor hereby grants to You a perpetual,
|
||||||
|
worldwide, non-exclusive, no-charge, royalty-free, irrevocable
|
||||||
|
(except as stated in this section) patent license to make, have made,
|
||||||
|
use, offer to sell, sell, import, and otherwise transfer the Work,
|
||||||
|
where such license applies only to those patent claims licensable
|
||||||
|
by such Contributor that are necessarily infringed by their
|
||||||
|
Contribution(s) alone or by combination of their Contribution(s)
|
||||||
|
with the Work to which such Contribution(s) was submitted. If You
|
||||||
|
institute patent litigation against any entity (including a
|
||||||
|
cross-claim or counterclaim in a lawsuit) alleging that the Work
|
||||||
|
or a Contribution incorporated within the Work constitutes direct
|
||||||
|
or contributory patent infringement, then any patent licenses
|
||||||
|
granted to You under this License for that Work shall terminate
|
||||||
|
as of the date such litigation is filed.
|
||||||
|
|
||||||
|
4. Redistribution. You may reproduce and distribute copies of the
|
||||||
|
Work or Derivative Works thereof in any medium, with or without
|
||||||
|
modifications, and in Source or Object form, provided that You
|
||||||
|
meet the following conditions:
|
||||||
|
|
||||||
|
(a) You must give any other recipients of the Work or
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||||||
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||||||
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|
||||||
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||||||
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||||||
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||||||
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||||||
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||||||
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||||||
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||||||
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||||||
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||||||
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||||||
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||||||
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||||||
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5. Submission of Contributions. Unless You explicitly state otherwise,
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||||||
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||||||
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||||||
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Notwithstanding the above, nothing herein shall supersede or modify
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||||||
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||||||
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||||||
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||||||
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||||||
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7. Disclaimer of Warranty. Unless required by applicable law or
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END OF TERMS AND CONDITIONS
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APPENDIX: How to apply the Apache License to your work.
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|
||||||
49
skills/.system/skill-creator/references/openai_yaml.md
Normal file
49
skills/.system/skill-creator/references/openai_yaml.md
Normal file
@ -0,0 +1,49 @@
|
|||||||
|
# openai.yaml fields (full example + descriptions)
|
||||||
|
|
||||||
|
`agents/openai.yaml` is an extended, product-specific config intended for the machine/harness to read, not the agent. Other product-specific config can also live in the `agents/` folder.
|
||||||
|
|
||||||
|
## Full example
|
||||||
|
|
||||||
|
```yaml
|
||||||
|
interface:
|
||||||
|
display_name: "Optional user-facing name"
|
||||||
|
short_description: "Optional user-facing description"
|
||||||
|
icon_small: "./assets/small-400px.png"
|
||||||
|
icon_large: "./assets/large-logo.svg"
|
||||||
|
brand_color: "#3B82F6"
|
||||||
|
default_prompt: "Optional surrounding prompt to use the skill with"
|
||||||
|
|
||||||
|
dependencies:
|
||||||
|
tools:
|
||||||
|
- type: "mcp"
|
||||||
|
value: "github"
|
||||||
|
description: "GitHub MCP server"
|
||||||
|
transport: "streamable_http"
|
||||||
|
url: "https://api.githubcopilot.com/mcp/"
|
||||||
|
|
||||||
|
policy:
|
||||||
|
allow_implicit_invocation: true
|
||||||
|
```
|
||||||
|
|
||||||
|
## Field descriptions and constraints
|
||||||
|
|
||||||
|
Top-level constraints:
|
||||||
|
|
||||||
|
- Quote all string values.
|
||||||
|
- Keep keys unquoted.
|
||||||
|
- For `interface.default_prompt`: generate a helpful, short (typically 1 sentence) example starting prompt based on the skill. It must explicitly mention the skill as `$skill-name` (e.g., "Use $skill-name-here to draft a concise weekly status update.").
|
||||||
|
|
||||||
|
- `interface.display_name`: Human-facing title shown in UI skill lists and chips.
|
||||||
|
- `interface.short_description`: Human-facing short UI blurb (25–64 chars) for quick scanning.
|
||||||
|
- `interface.icon_small`: Path to a small icon asset (relative to skill dir). Default to `./assets/` and place icons in the skill's `assets/` folder.
|
||||||
|
- `interface.icon_large`: Path to a larger logo asset (relative to skill dir). Default to `./assets/` and place icons in the skill's `assets/` folder.
|
||||||
|
- `interface.brand_color`: Hex color used for UI accents (e.g., badges).
|
||||||
|
- `interface.default_prompt`: Default prompt snippet inserted when invoking the skill.
|
||||||
|
- `dependencies.tools[].type`: Dependency category. Only `mcp` is supported for now.
|
||||||
|
- `dependencies.tools[].value`: Identifier of the tool or dependency.
|
||||||
|
- `dependencies.tools[].description`: Human-readable explanation of the dependency.
|
||||||
|
- `dependencies.tools[].transport`: Connection type when `type` is `mcp`.
|
||||||
|
- `dependencies.tools[].url`: MCP server URL when `type` is `mcp`.
|
||||||
|
- `policy.allow_implicit_invocation`: When false, the skill is not injected into
|
||||||
|
the model context by default, but can still be invoked explicitly via `$skill`.
|
||||||
|
Defaults to true.
|
||||||
226
skills/.system/skill-creator/scripts/generate_openai_yaml.py
Normal file
226
skills/.system/skill-creator/scripts/generate_openai_yaml.py
Normal file
@ -0,0 +1,226 @@
|
|||||||
|
#!/usr/bin/env python3
|
||||||
|
"""
|
||||||
|
OpenAI YAML Generator - Creates agents/openai.yaml for a skill folder.
|
||||||
|
|
||||||
|
Usage:
|
||||||
|
generate_openai_yaml.py <skill_dir> [--name <skill_name>] [--interface key=value]
|
||||||
|
"""
|
||||||
|
|
||||||
|
import argparse
|
||||||
|
import re
|
||||||
|
import sys
|
||||||
|
from pathlib import Path
|
||||||
|
|
||||||
|
ACRONYMS = {
|
||||||
|
"GH",
|
||||||
|
"MCP",
|
||||||
|
"API",
|
||||||
|
"CI",
|
||||||
|
"CLI",
|
||||||
|
"LLM",
|
||||||
|
"PDF",
|
||||||
|
"PR",
|
||||||
|
"UI",
|
||||||
|
"URL",
|
||||||
|
"SQL",
|
||||||
|
}
|
||||||
|
|
||||||
|
BRANDS = {
|
||||||
|
"openai": "OpenAI",
|
||||||
|
"openapi": "OpenAPI",
|
||||||
|
"github": "GitHub",
|
||||||
|
"pagerduty": "PagerDuty",
|
||||||
|
"datadog": "DataDog",
|
||||||
|
"sqlite": "SQLite",
|
||||||
|
"fastapi": "FastAPI",
|
||||||
|
}
|
||||||
|
|
||||||
|
SMALL_WORDS = {"and", "or", "to", "up", "with"}
|
||||||
|
|
||||||
|
ALLOWED_INTERFACE_KEYS = {
|
||||||
|
"display_name",
|
||||||
|
"short_description",
|
||||||
|
"icon_small",
|
||||||
|
"icon_large",
|
||||||
|
"brand_color",
|
||||||
|
"default_prompt",
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
def yaml_quote(value):
|
||||||
|
escaped = value.replace("\\", "\\\\").replace('"', '\\"').replace("\n", "\\n")
|
||||||
|
return f'"{escaped}"'
|
||||||
|
|
||||||
|
|
||||||
|
def format_display_name(skill_name):
|
||||||
|
words = [word for word in skill_name.split("-") if word]
|
||||||
|
formatted = []
|
||||||
|
for index, word in enumerate(words):
|
||||||
|
lower = word.lower()
|
||||||
|
upper = word.upper()
|
||||||
|
if upper in ACRONYMS:
|
||||||
|
formatted.append(upper)
|
||||||
|
continue
|
||||||
|
if lower in BRANDS:
|
||||||
|
formatted.append(BRANDS[lower])
|
||||||
|
continue
|
||||||
|
if index > 0 and lower in SMALL_WORDS:
|
||||||
|
formatted.append(lower)
|
||||||
|
continue
|
||||||
|
formatted.append(word.capitalize())
|
||||||
|
return " ".join(formatted)
|
||||||
|
|
||||||
|
|
||||||
|
def generate_short_description(display_name):
|
||||||
|
description = f"Help with {display_name} tasks"
|
||||||
|
|
||||||
|
if len(description) < 25:
|
||||||
|
description = f"Help with {display_name} tasks and workflows"
|
||||||
|
if len(description) < 25:
|
||||||
|
description = f"Help with {display_name} tasks with guidance"
|
||||||
|
|
||||||
|
if len(description) > 64:
|
||||||
|
description = f"Help with {display_name}"
|
||||||
|
if len(description) > 64:
|
||||||
|
description = f"{display_name} helper"
|
||||||
|
if len(description) > 64:
|
||||||
|
description = f"{display_name} tools"
|
||||||
|
if len(description) > 64:
|
||||||
|
suffix = " helper"
|
||||||
|
max_name_length = 64 - len(suffix)
|
||||||
|
trimmed = display_name[:max_name_length].rstrip()
|
||||||
|
description = f"{trimmed}{suffix}"
|
||||||
|
if len(description) > 64:
|
||||||
|
description = description[:64].rstrip()
|
||||||
|
|
||||||
|
if len(description) < 25:
|
||||||
|
description = f"{description} workflows"
|
||||||
|
if len(description) > 64:
|
||||||
|
description = description[:64].rstrip()
|
||||||
|
|
||||||
|
return description
|
||||||
|
|
||||||
|
|
||||||
|
def read_frontmatter_name(skill_dir):
|
||||||
|
skill_md = Path(skill_dir) / "SKILL.md"
|
||||||
|
if not skill_md.exists():
|
||||||
|
print(f"[ERROR] SKILL.md not found in {skill_dir}")
|
||||||
|
return None
|
||||||
|
content = skill_md.read_text()
|
||||||
|
match = re.match(r"^---\n(.*?)\n---", content, re.DOTALL)
|
||||||
|
if not match:
|
||||||
|
print("[ERROR] Invalid SKILL.md frontmatter format.")
|
||||||
|
return None
|
||||||
|
frontmatter_text = match.group(1)
|
||||||
|
|
||||||
|
import yaml
|
||||||
|
|
||||||
|
try:
|
||||||
|
frontmatter = yaml.safe_load(frontmatter_text)
|
||||||
|
except yaml.YAMLError as exc:
|
||||||
|
print(f"[ERROR] Invalid YAML frontmatter: {exc}")
|
||||||
|
return None
|
||||||
|
if not isinstance(frontmatter, dict):
|
||||||
|
print("[ERROR] Frontmatter must be a YAML dictionary.")
|
||||||
|
return None
|
||||||
|
name = frontmatter.get("name", "")
|
||||||
|
if not isinstance(name, str) or not name.strip():
|
||||||
|
print("[ERROR] Frontmatter 'name' is missing or invalid.")
|
||||||
|
return None
|
||||||
|
return name.strip()
|
||||||
|
|
||||||
|
|
||||||
|
def parse_interface_overrides(raw_overrides):
|
||||||
|
overrides = {}
|
||||||
|
optional_order = []
|
||||||
|
for item in raw_overrides:
|
||||||
|
if "=" not in item:
|
||||||
|
print(f"[ERROR] Invalid interface override '{item}'. Use key=value.")
|
||||||
|
return None, None
|
||||||
|
key, value = item.split("=", 1)
|
||||||
|
key = key.strip()
|
||||||
|
value = value.strip()
|
||||||
|
if not key:
|
||||||
|
print(f"[ERROR] Invalid interface override '{item}'. Key is empty.")
|
||||||
|
return None, None
|
||||||
|
if key not in ALLOWED_INTERFACE_KEYS:
|
||||||
|
allowed = ", ".join(sorted(ALLOWED_INTERFACE_KEYS))
|
||||||
|
print(f"[ERROR] Unknown interface field '{key}'. Allowed: {allowed}")
|
||||||
|
return None, None
|
||||||
|
overrides[key] = value
|
||||||
|
if key not in ("display_name", "short_description") and key not in optional_order:
|
||||||
|
optional_order.append(key)
|
||||||
|
return overrides, optional_order
|
||||||
|
|
||||||
|
|
||||||
|
def write_openai_yaml(skill_dir, skill_name, raw_overrides):
|
||||||
|
overrides, optional_order = parse_interface_overrides(raw_overrides)
|
||||||
|
if overrides is None:
|
||||||
|
return None
|
||||||
|
|
||||||
|
display_name = overrides.get("display_name") or format_display_name(skill_name)
|
||||||
|
short_description = overrides.get("short_description") or generate_short_description(display_name)
|
||||||
|
|
||||||
|
if not (25 <= len(short_description) <= 64):
|
||||||
|
print(
|
||||||
|
"[ERROR] short_description must be 25-64 characters "
|
||||||
|
f"(got {len(short_description)})."
|
||||||
|
)
|
||||||
|
return None
|
||||||
|
|
||||||
|
interface_lines = [
|
||||||
|
"interface:",
|
||||||
|
f" display_name: {yaml_quote(display_name)}",
|
||||||
|
f" short_description: {yaml_quote(short_description)}",
|
||||||
|
]
|
||||||
|
|
||||||
|
for key in optional_order:
|
||||||
|
value = overrides.get(key)
|
||||||
|
if value is not None:
|
||||||
|
interface_lines.append(f" {key}: {yaml_quote(value)}")
|
||||||
|
|
||||||
|
agents_dir = Path(skill_dir) / "agents"
|
||||||
|
agents_dir.mkdir(parents=True, exist_ok=True)
|
||||||
|
output_path = agents_dir / "openai.yaml"
|
||||||
|
output_path.write_text("\n".join(interface_lines) + "\n")
|
||||||
|
print(f"[OK] Created agents/openai.yaml")
|
||||||
|
return output_path
|
||||||
|
|
||||||
|
|
||||||
|
def main():
|
||||||
|
parser = argparse.ArgumentParser(
|
||||||
|
description="Create agents/openai.yaml for a skill directory.",
|
||||||
|
)
|
||||||
|
parser.add_argument("skill_dir", help="Path to the skill directory")
|
||||||
|
parser.add_argument(
|
||||||
|
"--name",
|
||||||
|
help="Skill name override (defaults to SKILL.md frontmatter)",
|
||||||
|
)
|
||||||
|
parser.add_argument(
|
||||||
|
"--interface",
|
||||||
|
action="append",
|
||||||
|
default=[],
|
||||||
|
help="Interface override in key=value format (repeatable)",
|
||||||
|
)
|
||||||
|
args = parser.parse_args()
|
||||||
|
|
||||||
|
skill_dir = Path(args.skill_dir).resolve()
|
||||||
|
if not skill_dir.exists():
|
||||||
|
print(f"[ERROR] Skill directory not found: {skill_dir}")
|
||||||
|
sys.exit(1)
|
||||||
|
if not skill_dir.is_dir():
|
||||||
|
print(f"[ERROR] Path is not a directory: {skill_dir}")
|
||||||
|
sys.exit(1)
|
||||||
|
|
||||||
|
skill_name = args.name or read_frontmatter_name(skill_dir)
|
||||||
|
if not skill_name:
|
||||||
|
sys.exit(1)
|
||||||
|
|
||||||
|
result = write_openai_yaml(skill_dir, skill_name, args.interface)
|
||||||
|
if result:
|
||||||
|
sys.exit(0)
|
||||||
|
sys.exit(1)
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
main()
|
||||||
400
skills/.system/skill-creator/scripts/init_skill.py
Normal file
400
skills/.system/skill-creator/scripts/init_skill.py
Normal file
@ -0,0 +1,400 @@
|
|||||||
|
#!/usr/bin/env python3
|
||||||
|
"""
|
||||||
|
Skill Initializer - Creates a new skill from template
|
||||||
|
|
||||||
|
Usage:
|
||||||
|
init_skill.py <skill-name> --path <path> [--resources scripts,references,assets] [--examples] [--interface key=value]
|
||||||
|
|
||||||
|
Examples:
|
||||||
|
init_skill.py my-new-skill --path skills/public
|
||||||
|
init_skill.py my-new-skill --path skills/public --resources scripts,references
|
||||||
|
init_skill.py my-api-helper --path skills/private --resources scripts --examples
|
||||||
|
init_skill.py custom-skill --path /custom/location
|
||||||
|
init_skill.py my-skill --path skills/public --interface short_description="Short UI label"
|
||||||
|
"""
|
||||||
|
|
||||||
|
import argparse
|
||||||
|
import re
|
||||||
|
import sys
|
||||||
|
from pathlib import Path
|
||||||
|
|
||||||
|
from generate_openai_yaml import write_openai_yaml
|
||||||
|
|
||||||
|
MAX_SKILL_NAME_LENGTH = 64
|
||||||
|
ALLOWED_RESOURCES = {"scripts", "references", "assets"}
|
||||||
|
|
||||||
|
SKILL_TEMPLATE = """---
|
||||||
|
name: {skill_name}
|
||||||
|
description: [TODO: Complete and informative explanation of what the skill does and when to use it. Include WHEN to use this skill - specific scenarios, file types, or tasks that trigger it.]
|
||||||
|
---
|
||||||
|
|
||||||
|
# {skill_title}
|
||||||
|
|
||||||
|
## Overview
|
||||||
|
|
||||||
|
[TODO: 1-2 sentences explaining what this skill enables]
|
||||||
|
|
||||||
|
## Structuring This Skill
|
||||||
|
|
||||||
|
[TODO: Choose the structure that best fits this skill's purpose. Common patterns:
|
||||||
|
|
||||||
|
**1. Workflow-Based** (best for sequential processes)
|
||||||
|
- Works well when there are clear step-by-step procedures
|
||||||
|
- Example: DOCX skill with "Workflow Decision Tree" -> "Reading" -> "Creating" -> "Editing"
|
||||||
|
- Structure: ## Overview -> ## Workflow Decision Tree -> ## Step 1 -> ## Step 2...
|
||||||
|
|
||||||
|
**2. Task-Based** (best for tool collections)
|
||||||
|
- Works well when the skill offers different operations/capabilities
|
||||||
|
- Example: PDF skill with "Quick Start" -> "Merge PDFs" -> "Split PDFs" -> "Extract Text"
|
||||||
|
- Structure: ## Overview -> ## Quick Start -> ## Task Category 1 -> ## Task Category 2...
|
||||||
|
|
||||||
|
**3. Reference/Guidelines** (best for standards or specifications)
|
||||||
|
- Works well for brand guidelines, coding standards, or requirements
|
||||||
|
- Example: Brand styling with "Brand Guidelines" -> "Colors" -> "Typography" -> "Features"
|
||||||
|
- Structure: ## Overview -> ## Guidelines -> ## Specifications -> ## Usage...
|
||||||
|
|
||||||
|
**4. Capabilities-Based** (best for integrated systems)
|
||||||
|
- Works well when the skill provides multiple interrelated features
|
||||||
|
- Example: Product Management with "Core Capabilities" -> numbered capability list
|
||||||
|
- Structure: ## Overview -> ## Core Capabilities -> ### 1. Feature -> ### 2. Feature...
|
||||||
|
|
||||||
|
Patterns can be mixed and matched as needed. Most skills combine patterns (e.g., start with task-based, add workflow for complex operations).
|
||||||
|
|
||||||
|
Delete this entire "Structuring This Skill" section when done - it's just guidance.]
|
||||||
|
|
||||||
|
## [TODO: Replace with the first main section based on chosen structure]
|
||||||
|
|
||||||
|
[TODO: Add content here. See examples in existing skills:
|
||||||
|
- Code samples for technical skills
|
||||||
|
- Decision trees for complex workflows
|
||||||
|
- Concrete examples with realistic user requests
|
||||||
|
- References to scripts/templates/references as needed]
|
||||||
|
|
||||||
|
## Resources (optional)
|
||||||
|
|
||||||
|
Create only the resource directories this skill actually needs. Delete this section if no resources are required.
|
||||||
|
|
||||||
|
### scripts/
|
||||||
|
Executable code (Python/Bash/etc.) that can be run directly to perform specific operations.
|
||||||
|
|
||||||
|
**Examples from other skills:**
|
||||||
|
- PDF skill: `fill_fillable_fields.py`, `extract_form_field_info.py` - utilities for PDF manipulation
|
||||||
|
- DOCX skill: `document.py`, `utilities.py` - Python modules for document processing
|
||||||
|
|
||||||
|
**Appropriate for:** Python scripts, shell scripts, or any executable code that performs automation, data processing, or specific operations.
|
||||||
|
|
||||||
|
**Note:** Scripts may be executed without loading into context, but can still be read by Codex for patching or environment adjustments.
|
||||||
|
|
||||||
|
### references/
|
||||||
|
Documentation and reference material intended to be loaded into context to inform Codex's process and thinking.
|
||||||
|
|
||||||
|
**Examples from other skills:**
|
||||||
|
- Product management: `communication.md`, `context_building.md` - detailed workflow guides
|
||||||
|
- BigQuery: API reference documentation and query examples
|
||||||
|
- Finance: Schema documentation, company policies
|
||||||
|
|
||||||
|
**Appropriate for:** In-depth documentation, API references, database schemas, comprehensive guides, or any detailed information that Codex should reference while working.
|
||||||
|
|
||||||
|
### assets/
|
||||||
|
Files not intended to be loaded into context, but rather used within the output Codex produces.
|
||||||
|
|
||||||
|
**Examples from other skills:**
|
||||||
|
- Brand styling: PowerPoint template files (.pptx), logo files
|
||||||
|
- Frontend builder: HTML/React boilerplate project directories
|
||||||
|
- Typography: Font files (.ttf, .woff2)
|
||||||
|
|
||||||
|
**Appropriate for:** Templates, boilerplate code, document templates, images, icons, fonts, or any files meant to be copied or used in the final output.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
**Not every skill requires all three types of resources.**
|
||||||
|
"""
|
||||||
|
|
||||||
|
EXAMPLE_SCRIPT = '''#!/usr/bin/env python3
|
||||||
|
"""
|
||||||
|
Example helper script for {skill_name}
|
||||||
|
|
||||||
|
This is a placeholder script that can be executed directly.
|
||||||
|
Replace with actual implementation or delete if not needed.
|
||||||
|
|
||||||
|
Example real scripts from other skills:
|
||||||
|
- pdf/scripts/fill_fillable_fields.py - Fills PDF form fields
|
||||||
|
- pdf/scripts/convert_pdf_to_images.py - Converts PDF pages to images
|
||||||
|
"""
|
||||||
|
|
||||||
|
def main():
|
||||||
|
print("This is an example script for {skill_name}")
|
||||||
|
# TODO: Add actual script logic here
|
||||||
|
# This could be data processing, file conversion, API calls, etc.
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
main()
|
||||||
|
'''
|
||||||
|
|
||||||
|
EXAMPLE_REFERENCE = """# Reference Documentation for {skill_title}
|
||||||
|
|
||||||
|
This is a placeholder for detailed reference documentation.
|
||||||
|
Replace with actual reference content or delete if not needed.
|
||||||
|
|
||||||
|
Example real reference docs from other skills:
|
||||||
|
- product-management/references/communication.md - Comprehensive guide for status updates
|
||||||
|
- product-management/references/context_building.md - Deep-dive on gathering context
|
||||||
|
- bigquery/references/ - API references and query examples
|
||||||
|
|
||||||
|
## When Reference Docs Are Useful
|
||||||
|
|
||||||
|
Reference docs are ideal for:
|
||||||
|
- Comprehensive API documentation
|
||||||
|
- Detailed workflow guides
|
||||||
|
- Complex multi-step processes
|
||||||
|
- Information too lengthy for main SKILL.md
|
||||||
|
- Content that's only needed for specific use cases
|
||||||
|
|
||||||
|
## Structure Suggestions
|
||||||
|
|
||||||
|
### API Reference Example
|
||||||
|
- Overview
|
||||||
|
- Authentication
|
||||||
|
- Endpoints with examples
|
||||||
|
- Error codes
|
||||||
|
- Rate limits
|
||||||
|
|
||||||
|
### Workflow Guide Example
|
||||||
|
- Prerequisites
|
||||||
|
- Step-by-step instructions
|
||||||
|
- Common patterns
|
||||||
|
- Troubleshooting
|
||||||
|
- Best practices
|
||||||
|
"""
|
||||||
|
|
||||||
|
EXAMPLE_ASSET = """# Example Asset File
|
||||||
|
|
||||||
|
This placeholder represents where asset files would be stored.
|
||||||
|
Replace with actual asset files (templates, images, fonts, etc.) or delete if not needed.
|
||||||
|
|
||||||
|
Asset files are NOT intended to be loaded into context, but rather used within
|
||||||
|
the output Codex produces.
|
||||||
|
|
||||||
|
Example asset files from other skills:
|
||||||
|
- Brand guidelines: logo.png, slides_template.pptx
|
||||||
|
- Frontend builder: hello-world/ directory with HTML/React boilerplate
|
||||||
|
- Typography: custom-font.ttf, font-family.woff2
|
||||||
|
- Data: sample_data.csv, test_dataset.json
|
||||||
|
|
||||||
|
## Common Asset Types
|
||||||
|
|
||||||
|
- Templates: .pptx, .docx, boilerplate directories
|
||||||
|
- Images: .png, .jpg, .svg, .gif
|
||||||
|
- Fonts: .ttf, .otf, .woff, .woff2
|
||||||
|
- Boilerplate code: Project directories, starter files
|
||||||
|
- Icons: .ico, .svg
|
||||||
|
- Data files: .csv, .json, .xml, .yaml
|
||||||
|
|
||||||
|
Note: This is a text placeholder. Actual assets can be any file type.
|
||||||
|
"""
|
||||||
|
|
||||||
|
|
||||||
|
def normalize_skill_name(skill_name):
|
||||||
|
"""Normalize a skill name to lowercase hyphen-case."""
|
||||||
|
normalized = skill_name.strip().lower()
|
||||||
|
normalized = re.sub(r"[^a-z0-9]+", "-", normalized)
|
||||||
|
normalized = normalized.strip("-")
|
||||||
|
normalized = re.sub(r"-{2,}", "-", normalized)
|
||||||
|
return normalized
|
||||||
|
|
||||||
|
|
||||||
|
def title_case_skill_name(skill_name):
|
||||||
|
"""Convert hyphenated skill name to Title Case for display."""
|
||||||
|
return " ".join(word.capitalize() for word in skill_name.split("-"))
|
||||||
|
|
||||||
|
|
||||||
|
def parse_resources(raw_resources):
|
||||||
|
if not raw_resources:
|
||||||
|
return []
|
||||||
|
resources = [item.strip() for item in raw_resources.split(",") if item.strip()]
|
||||||
|
invalid = sorted({item for item in resources if item not in ALLOWED_RESOURCES})
|
||||||
|
if invalid:
|
||||||
|
allowed = ", ".join(sorted(ALLOWED_RESOURCES))
|
||||||
|
print(f"[ERROR] Unknown resource type(s): {', '.join(invalid)}")
|
||||||
|
print(f" Allowed: {allowed}")
|
||||||
|
sys.exit(1)
|
||||||
|
deduped = []
|
||||||
|
seen = set()
|
||||||
|
for resource in resources:
|
||||||
|
if resource not in seen:
|
||||||
|
deduped.append(resource)
|
||||||
|
seen.add(resource)
|
||||||
|
return deduped
|
||||||
|
|
||||||
|
|
||||||
|
def create_resource_dirs(skill_dir, skill_name, skill_title, resources, include_examples):
|
||||||
|
for resource in resources:
|
||||||
|
resource_dir = skill_dir / resource
|
||||||
|
resource_dir.mkdir(exist_ok=True)
|
||||||
|
if resource == "scripts":
|
||||||
|
if include_examples:
|
||||||
|
example_script = resource_dir / "example.py"
|
||||||
|
example_script.write_text(EXAMPLE_SCRIPT.format(skill_name=skill_name))
|
||||||
|
example_script.chmod(0o755)
|
||||||
|
print("[OK] Created scripts/example.py")
|
||||||
|
else:
|
||||||
|
print("[OK] Created scripts/")
|
||||||
|
elif resource == "references":
|
||||||
|
if include_examples:
|
||||||
|
example_reference = resource_dir / "api_reference.md"
|
||||||
|
example_reference.write_text(EXAMPLE_REFERENCE.format(skill_title=skill_title))
|
||||||
|
print("[OK] Created references/api_reference.md")
|
||||||
|
else:
|
||||||
|
print("[OK] Created references/")
|
||||||
|
elif resource == "assets":
|
||||||
|
if include_examples:
|
||||||
|
example_asset = resource_dir / "example_asset.txt"
|
||||||
|
example_asset.write_text(EXAMPLE_ASSET)
|
||||||
|
print("[OK] Created assets/example_asset.txt")
|
||||||
|
else:
|
||||||
|
print("[OK] Created assets/")
|
||||||
|
|
||||||
|
|
||||||
|
def init_skill(skill_name, path, resources, include_examples, interface_overrides):
|
||||||
|
"""
|
||||||
|
Initialize a new skill directory with template SKILL.md.
|
||||||
|
|
||||||
|
Args:
|
||||||
|
skill_name: Name of the skill
|
||||||
|
path: Path where the skill directory should be created
|
||||||
|
resources: Resource directories to create
|
||||||
|
include_examples: Whether to create example files in resource directories
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
Path to created skill directory, or None if error
|
||||||
|
"""
|
||||||
|
# Determine skill directory path
|
||||||
|
skill_dir = Path(path).resolve() / skill_name
|
||||||
|
|
||||||
|
# Check if directory already exists
|
||||||
|
if skill_dir.exists():
|
||||||
|
print(f"[ERROR] Skill directory already exists: {skill_dir}")
|
||||||
|
return None
|
||||||
|
|
||||||
|
# Create skill directory
|
||||||
|
try:
|
||||||
|
skill_dir.mkdir(parents=True, exist_ok=False)
|
||||||
|
print(f"[OK] Created skill directory: {skill_dir}")
|
||||||
|
except Exception as e:
|
||||||
|
print(f"[ERROR] Error creating directory: {e}")
|
||||||
|
return None
|
||||||
|
|
||||||
|
# Create SKILL.md from template
|
||||||
|
skill_title = title_case_skill_name(skill_name)
|
||||||
|
skill_content = SKILL_TEMPLATE.format(skill_name=skill_name, skill_title=skill_title)
|
||||||
|
|
||||||
|
skill_md_path = skill_dir / "SKILL.md"
|
||||||
|
try:
|
||||||
|
skill_md_path.write_text(skill_content)
|
||||||
|
print("[OK] Created SKILL.md")
|
||||||
|
except Exception as e:
|
||||||
|
print(f"[ERROR] Error creating SKILL.md: {e}")
|
||||||
|
return None
|
||||||
|
|
||||||
|
# Create agents/openai.yaml
|
||||||
|
try:
|
||||||
|
result = write_openai_yaml(skill_dir, skill_name, interface_overrides)
|
||||||
|
if not result:
|
||||||
|
return None
|
||||||
|
except Exception as e:
|
||||||
|
print(f"[ERROR] Error creating agents/openai.yaml: {e}")
|
||||||
|
return None
|
||||||
|
|
||||||
|
# Create resource directories if requested
|
||||||
|
if resources:
|
||||||
|
try:
|
||||||
|
create_resource_dirs(skill_dir, skill_name, skill_title, resources, include_examples)
|
||||||
|
except Exception as e:
|
||||||
|
print(f"[ERROR] Error creating resource directories: {e}")
|
||||||
|
return None
|
||||||
|
|
||||||
|
# Print next steps
|
||||||
|
print(f"\n[OK] Skill '{skill_name}' initialized successfully at {skill_dir}")
|
||||||
|
print("\nNext steps:")
|
||||||
|
print("1. Edit SKILL.md to complete the TODO items and update the description")
|
||||||
|
if resources:
|
||||||
|
if include_examples:
|
||||||
|
print("2. Customize or delete the example files in scripts/, references/, and assets/")
|
||||||
|
else:
|
||||||
|
print("2. Add resources to scripts/, references/, and assets/ as needed")
|
||||||
|
else:
|
||||||
|
print("2. Create resource directories only if needed (scripts/, references/, assets/)")
|
||||||
|
print("3. Update agents/openai.yaml if the UI metadata should differ")
|
||||||
|
print("4. Run the validator when ready to check the skill structure")
|
||||||
|
print(
|
||||||
|
"5. Forward-test complex skills with realistic user requests to ensure they work as intended"
|
||||||
|
)
|
||||||
|
|
||||||
|
return skill_dir
|
||||||
|
|
||||||
|
|
||||||
|
def main():
|
||||||
|
parser = argparse.ArgumentParser(
|
||||||
|
description="Create a new skill directory with a SKILL.md template.",
|
||||||
|
)
|
||||||
|
parser.add_argument("skill_name", help="Skill name (normalized to hyphen-case)")
|
||||||
|
parser.add_argument("--path", required=True, help="Output directory for the skill")
|
||||||
|
parser.add_argument(
|
||||||
|
"--resources",
|
||||||
|
default="",
|
||||||
|
help="Comma-separated list: scripts,references,assets",
|
||||||
|
)
|
||||||
|
parser.add_argument(
|
||||||
|
"--examples",
|
||||||
|
action="store_true",
|
||||||
|
help="Create example files inside the selected resource directories",
|
||||||
|
)
|
||||||
|
parser.add_argument(
|
||||||
|
"--interface",
|
||||||
|
action="append",
|
||||||
|
default=[],
|
||||||
|
help="Interface override in key=value format (repeatable)",
|
||||||
|
)
|
||||||
|
args = parser.parse_args()
|
||||||
|
|
||||||
|
raw_skill_name = args.skill_name
|
||||||
|
skill_name = normalize_skill_name(raw_skill_name)
|
||||||
|
if not skill_name:
|
||||||
|
print("[ERROR] Skill name must include at least one letter or digit.")
|
||||||
|
sys.exit(1)
|
||||||
|
if len(skill_name) > MAX_SKILL_NAME_LENGTH:
|
||||||
|
print(
|
||||||
|
f"[ERROR] Skill name '{skill_name}' is too long ({len(skill_name)} characters). "
|
||||||
|
f"Maximum is {MAX_SKILL_NAME_LENGTH} characters."
|
||||||
|
)
|
||||||
|
sys.exit(1)
|
||||||
|
if skill_name != raw_skill_name:
|
||||||
|
print(f"Note: Normalized skill name from '{raw_skill_name}' to '{skill_name}'.")
|
||||||
|
|
||||||
|
resources = parse_resources(args.resources)
|
||||||
|
if args.examples and not resources:
|
||||||
|
print("[ERROR] --examples requires --resources to be set.")
|
||||||
|
sys.exit(1)
|
||||||
|
|
||||||
|
path = args.path
|
||||||
|
|
||||||
|
print(f"Initializing skill: {skill_name}")
|
||||||
|
print(f" Location: {path}")
|
||||||
|
if resources:
|
||||||
|
print(f" Resources: {', '.join(resources)}")
|
||||||
|
if args.examples:
|
||||||
|
print(" Examples: enabled")
|
||||||
|
else:
|
||||||
|
print(" Resources: none (create as needed)")
|
||||||
|
print()
|
||||||
|
|
||||||
|
result = init_skill(skill_name, path, resources, args.examples, args.interface)
|
||||||
|
|
||||||
|
if result:
|
||||||
|
sys.exit(0)
|
||||||
|
else:
|
||||||
|
sys.exit(1)
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
main()
|
||||||
101
skills/.system/skill-creator/scripts/quick_validate.py
Normal file
101
skills/.system/skill-creator/scripts/quick_validate.py
Normal file
@ -0,0 +1,101 @@
|
|||||||
|
#!/usr/bin/env python3
|
||||||
|
"""
|
||||||
|
Quick validation script for skills - minimal version
|
||||||
|
"""
|
||||||
|
|
||||||
|
import re
|
||||||
|
import sys
|
||||||
|
from pathlib import Path
|
||||||
|
|
||||||
|
import yaml
|
||||||
|
|
||||||
|
MAX_SKILL_NAME_LENGTH = 64
|
||||||
|
|
||||||
|
|
||||||
|
def validate_skill(skill_path):
|
||||||
|
"""Basic validation of a skill"""
|
||||||
|
skill_path = Path(skill_path)
|
||||||
|
|
||||||
|
skill_md = skill_path / "SKILL.md"
|
||||||
|
if not skill_md.exists():
|
||||||
|
return False, "SKILL.md not found"
|
||||||
|
|
||||||
|
content = skill_md.read_text()
|
||||||
|
if not content.startswith("---"):
|
||||||
|
return False, "No YAML frontmatter found"
|
||||||
|
|
||||||
|
match = re.match(r"^---\n(.*?)\n---", content, re.DOTALL)
|
||||||
|
if not match:
|
||||||
|
return False, "Invalid frontmatter format"
|
||||||
|
|
||||||
|
frontmatter_text = match.group(1)
|
||||||
|
|
||||||
|
try:
|
||||||
|
frontmatter = yaml.safe_load(frontmatter_text)
|
||||||
|
if not isinstance(frontmatter, dict):
|
||||||
|
return False, "Frontmatter must be a YAML dictionary"
|
||||||
|
except yaml.YAMLError as e:
|
||||||
|
return False, f"Invalid YAML in frontmatter: {e}"
|
||||||
|
|
||||||
|
allowed_properties = {"name", "description", "license", "allowed-tools", "metadata"}
|
||||||
|
|
||||||
|
unexpected_keys = set(frontmatter.keys()) - allowed_properties
|
||||||
|
if unexpected_keys:
|
||||||
|
allowed = ", ".join(sorted(allowed_properties))
|
||||||
|
unexpected = ", ".join(sorted(unexpected_keys))
|
||||||
|
return (
|
||||||
|
False,
|
||||||
|
f"Unexpected key(s) in SKILL.md frontmatter: {unexpected}. Allowed properties are: {allowed}",
|
||||||
|
)
|
||||||
|
|
||||||
|
if "name" not in frontmatter:
|
||||||
|
return False, "Missing 'name' in frontmatter"
|
||||||
|
if "description" not in frontmatter:
|
||||||
|
return False, "Missing 'description' in frontmatter"
|
||||||
|
|
||||||
|
name = frontmatter.get("name", "")
|
||||||
|
if not isinstance(name, str):
|
||||||
|
return False, f"Name must be a string, got {type(name).__name__}"
|
||||||
|
name = name.strip()
|
||||||
|
if name:
|
||||||
|
if not re.match(r"^[a-z0-9-]+$", name):
|
||||||
|
return (
|
||||||
|
False,
|
||||||
|
f"Name '{name}' should be hyphen-case (lowercase letters, digits, and hyphens only)",
|
||||||
|
)
|
||||||
|
if name.startswith("-") or name.endswith("-") or "--" in name:
|
||||||
|
return (
|
||||||
|
False,
|
||||||
|
f"Name '{name}' cannot start/end with hyphen or contain consecutive hyphens",
|
||||||
|
)
|
||||||
|
if len(name) > MAX_SKILL_NAME_LENGTH:
|
||||||
|
return (
|
||||||
|
False,
|
||||||
|
f"Name is too long ({len(name)} characters). "
|
||||||
|
f"Maximum is {MAX_SKILL_NAME_LENGTH} characters.",
|
||||||
|
)
|
||||||
|
|
||||||
|
description = frontmatter.get("description", "")
|
||||||
|
if not isinstance(description, str):
|
||||||
|
return False, f"Description must be a string, got {type(description).__name__}"
|
||||||
|
description = description.strip()
|
||||||
|
if description:
|
||||||
|
if "<" in description or ">" in description:
|
||||||
|
return False, "Description cannot contain angle brackets (< or >)"
|
||||||
|
if len(description) > 1024:
|
||||||
|
return (
|
||||||
|
False,
|
||||||
|
f"Description is too long ({len(description)} characters). Maximum is 1024 characters.",
|
||||||
|
)
|
||||||
|
|
||||||
|
return True, "Skill is valid!"
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
if len(sys.argv) != 2:
|
||||||
|
print("Usage: python quick_validate.py <skill_directory>")
|
||||||
|
sys.exit(1)
|
||||||
|
|
||||||
|
valid, message = validate_skill(sys.argv[1])
|
||||||
|
print(message)
|
||||||
|
sys.exit(0 if valid else 1)
|
||||||
202
skills/.system/skill-installer/LICENSE.txt
Normal file
202
skills/.system/skill-installer/LICENSE.txt
Normal file
@ -0,0 +1,202 @@
|
|||||||
|
|
||||||
|
Apache License
|
||||||
|
Version 2.0, January 2004
|
||||||
|
http://www.apache.org/licenses/
|
||||||
|
|
||||||
|
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
|
||||||
|
|
||||||
|
1. Definitions.
|
||||||
|
|
||||||
|
"License" shall mean the terms and conditions for use, reproduction,
|
||||||
|
and distribution as defined by Sections 1 through 9 of this document.
|
||||||
|
|
||||||
|
"Licensor" shall mean the copyright owner or entity authorized by
|
||||||
|
the copyright owner that is granting the License.
|
||||||
|
|
||||||
|
"Legal Entity" shall mean the union of the acting entity and all
|
||||||
|
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|
||||||
|
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|
||||||
|
"control" means (i) the power, direct or indirect, to cause the
|
||||||
|
direction or management of such entity, whether by contract or
|
||||||
|
otherwise, or (ii) ownership of fifty percent (50%) or more of the
|
||||||
|
outstanding shares, or (iii) beneficial ownership of such entity.
|
||||||
|
|
||||||
|
"You" (or "Your") shall mean an individual or Legal Entity
|
||||||
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|
||||||
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|
||||||
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||||||
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|
||||||
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"Object" form shall mean any form resulting from mechanical
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||||||
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(d) If the Work includes a "NOTICE" text file as part of its
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APPENDIX: How to apply the Apache License to your work.
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||||||
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|
||||||
58
skills/.system/skill-installer/SKILL.md
Normal file
58
skills/.system/skill-installer/SKILL.md
Normal file
@ -0,0 +1,58 @@
|
|||||||
|
---
|
||||||
|
name: skill-installer
|
||||||
|
description: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos).
|
||||||
|
metadata:
|
||||||
|
short-description: Install curated skills from openai/skills or other repos
|
||||||
|
---
|
||||||
|
|
||||||
|
# Skill Installer
|
||||||
|
|
||||||
|
Helps install skills. By default these are from https://github.com/openai/skills/tree/main/skills/.curated, but users can also provide other locations. Experimental skills live in https://github.com/openai/skills/tree/main/skills/.experimental and can be installed the same way.
|
||||||
|
|
||||||
|
Use the helper scripts based on the task:
|
||||||
|
- List skills when the user asks what is available, or if the user uses this skill without specifying what to do. Default listing is `.curated`, but you can pass `--path skills/.experimental` when they ask about experimental skills.
|
||||||
|
- Install from the curated list when the user provides a skill name.
|
||||||
|
- Install from another repo when the user provides a GitHub repo/path (including private repos).
|
||||||
|
|
||||||
|
Install skills with the helper scripts.
|
||||||
|
|
||||||
|
## Communication
|
||||||
|
|
||||||
|
When listing skills, output approximately as follows, depending on the context of the user's request. If they ask about experimental skills, list from `.experimental` instead of `.curated` and label the source accordingly:
|
||||||
|
"""
|
||||||
|
Skills from {repo}:
|
||||||
|
1. skill-1
|
||||||
|
2. skill-2 (already installed)
|
||||||
|
3. ...
|
||||||
|
Which ones would you like installed?
|
||||||
|
"""
|
||||||
|
|
||||||
|
After installing a skill, tell the user it will be available on their next turn.
|
||||||
|
|
||||||
|
## Scripts
|
||||||
|
|
||||||
|
All of these scripts use network, so when running in the sandbox, request escalation when running them.
|
||||||
|
|
||||||
|
- `scripts/list-skills.py` (prints skills list with installed annotations)
|
||||||
|
- `scripts/list-skills.py --format json`
|
||||||
|
- Example (experimental list): `scripts/list-skills.py --path skills/.experimental`
|
||||||
|
- `scripts/install-skill-from-github.py --repo <owner>/<repo> --path <path/to/skill> [<path/to/skill> ...]`
|
||||||
|
- `scripts/install-skill-from-github.py --url https://github.com/<owner>/<repo>/tree/<ref>/<path>`
|
||||||
|
- Example (experimental skill): `scripts/install-skill-from-github.py --repo openai/skills --path skills/.experimental/<skill-name>`
|
||||||
|
|
||||||
|
## Behavior and Options
|
||||||
|
|
||||||
|
- Defaults to direct download for public GitHub repos.
|
||||||
|
- If download fails with auth/permission errors, falls back to git sparse checkout.
|
||||||
|
- Aborts if the destination skill directory already exists.
|
||||||
|
- Installs into `$CODEX_HOME/skills/<skill-name>` (defaults to `~/.codex/skills`).
|
||||||
|
- Multiple `--path` values install multiple skills in one run, each named from the path basename unless `--name` is supplied.
|
||||||
|
- Options: `--ref <ref>` (default `main`), `--dest <path>`, `--method auto|download|git`.
|
||||||
|
|
||||||
|
## Notes
|
||||||
|
|
||||||
|
- Curated listing is fetched from `https://github.com/openai/skills/tree/main/skills/.curated` via the GitHub API. If it is unavailable, explain the error and exit.
|
||||||
|
- Private GitHub repos can be accessed via existing git credentials or optional `GITHUB_TOKEN`/`GH_TOKEN` for download.
|
||||||
|
- Git fallback tries HTTPS first, then SSH.
|
||||||
|
- The skills at https://github.com/openai/skills/tree/main/skills/.system are preinstalled, so no need to help users install those. If they ask, just explain this. If they insist, you can download and overwrite.
|
||||||
|
- Installed annotations come from `$CODEX_HOME/skills`.
|
||||||
5
skills/.system/skill-installer/agents/openai.yaml
Normal file
5
skills/.system/skill-installer/agents/openai.yaml
Normal file
@ -0,0 +1,5 @@
|
|||||||
|
interface:
|
||||||
|
display_name: "Skill Installer"
|
||||||
|
short_description: "Install curated skills from openai/skills or other repos"
|
||||||
|
icon_small: "./assets/skill-installer-small.svg"
|
||||||
|
icon_large: "./assets/skill-installer.png"
|
||||||
@ -0,0 +1,3 @@
|
|||||||
|
<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" fill="currentColor" viewBox="0 0 16 16">
|
||||||
|
<path fill="#0D0D0D" d="M2.145 3.959a2.033 2.033 0 0 1 2.022-1.824h5.966c.551 0 .997 0 1.357.029.367.03.692.093.993.246l.174.098c.397.243.72.593.932 1.01l.053.114c.116.269.168.557.194.878.03.36.03.805.03 1.357v4.3a2.365 2.365 0 0 1-2.366 2.365h-1.312a2.198 2.198 0 0 1-4.377 0H4.167A2.032 2.032 0 0 1 2.135 10.5V9.333l.004-.088A.865.865 0 0 1 3 8.468l.116-.006A1.135 1.135 0 0 0 3 6.199a.865.865 0 0 1-.865-.864V4.167l.01-.208Zm1.054 1.186a2.198 2.198 0 0 1 0 4.376v.98c0 .534.433.967.968.967H6l.089.004a.866.866 0 0 1 .776.861 1.135 1.135 0 0 0 2.27 0c0-.478.387-.865.865-.865h1.5c.719 0 1.301-.583 1.301-1.301v-4.3c0-.57 0-.964-.025-1.27a1.933 1.933 0 0 0-.09-.493L12.642 4a1.47 1.47 0 0 0-.541-.585l-.102-.056c-.126-.065-.295-.11-.596-.135a17.31 17.31 0 0 0-1.27-.025H4.167a.968.968 0 0 0-.968.968v.978Z"/>
|
||||||
|
</svg>
|
||||||
|
After Width: | Height: | Size: 923 B |
BIN
skills/.system/skill-installer/assets/skill-installer.png
Normal file
BIN
skills/.system/skill-installer/assets/skill-installer.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 1.1 KiB |
Binary file not shown.
21
skills/.system/skill-installer/scripts/github_utils.py
Normal file
21
skills/.system/skill-installer/scripts/github_utils.py
Normal file
@ -0,0 +1,21 @@
|
|||||||
|
#!/usr/bin/env python3
|
||||||
|
"""Shared GitHub helpers for skill install scripts."""
|
||||||
|
|
||||||
|
from __future__ import annotations
|
||||||
|
|
||||||
|
import os
|
||||||
|
import urllib.request
|
||||||
|
|
||||||
|
|
||||||
|
def github_request(url: str, user_agent: str) -> bytes:
|
||||||
|
headers = {"User-Agent": user_agent}
|
||||||
|
token = os.environ.get("GITHUB_TOKEN") or os.environ.get("GH_TOKEN")
|
||||||
|
if token:
|
||||||
|
headers["Authorization"] = f"token {token}"
|
||||||
|
req = urllib.request.Request(url, headers=headers)
|
||||||
|
with urllib.request.urlopen(req) as resp:
|
||||||
|
return resp.read()
|
||||||
|
|
||||||
|
|
||||||
|
def github_api_contents_url(repo: str, path: str, ref: str) -> str:
|
||||||
|
return f"https://api.github.com/repos/{repo}/contents/{path}?ref={ref}"
|
||||||
@ -0,0 +1,308 @@
|
|||||||
|
#!/usr/bin/env python3
|
||||||
|
"""Install a skill from a GitHub repo path into $CODEX_HOME/skills."""
|
||||||
|
|
||||||
|
from __future__ import annotations
|
||||||
|
|
||||||
|
import argparse
|
||||||
|
from dataclasses import dataclass
|
||||||
|
import os
|
||||||
|
import shutil
|
||||||
|
import subprocess
|
||||||
|
import sys
|
||||||
|
import tempfile
|
||||||
|
import urllib.error
|
||||||
|
import urllib.parse
|
||||||
|
import zipfile
|
||||||
|
|
||||||
|
from github_utils import github_request
|
||||||
|
DEFAULT_REF = "main"
|
||||||
|
|
||||||
|
|
||||||
|
@dataclass
|
||||||
|
class Args:
|
||||||
|
url: str | None = None
|
||||||
|
repo: str | None = None
|
||||||
|
path: list[str] | None = None
|
||||||
|
ref: str = DEFAULT_REF
|
||||||
|
dest: str | None = None
|
||||||
|
name: str | None = None
|
||||||
|
method: str = "auto"
|
||||||
|
|
||||||
|
|
||||||
|
@dataclass
|
||||||
|
class Source:
|
||||||
|
owner: str
|
||||||
|
repo: str
|
||||||
|
ref: str
|
||||||
|
paths: list[str]
|
||||||
|
repo_url: str | None = None
|
||||||
|
|
||||||
|
|
||||||
|
class InstallError(Exception):
|
||||||
|
pass
|
||||||
|
|
||||||
|
|
||||||
|
def _codex_home() -> str:
|
||||||
|
return os.environ.get("CODEX_HOME", os.path.expanduser("~/.codex"))
|
||||||
|
|
||||||
|
|
||||||
|
def _tmp_root() -> str:
|
||||||
|
base = os.path.join(tempfile.gettempdir(), "codex")
|
||||||
|
os.makedirs(base, exist_ok=True)
|
||||||
|
return base
|
||||||
|
|
||||||
|
|
||||||
|
def _request(url: str) -> bytes:
|
||||||
|
return github_request(url, "codex-skill-install")
|
||||||
|
|
||||||
|
|
||||||
|
def _parse_github_url(url: str, default_ref: str) -> tuple[str, str, str, str | None]:
|
||||||
|
parsed = urllib.parse.urlparse(url)
|
||||||
|
if parsed.netloc != "github.com":
|
||||||
|
raise InstallError("Only GitHub URLs are supported for download mode.")
|
||||||
|
parts = [p for p in parsed.path.split("/") if p]
|
||||||
|
if len(parts) < 2:
|
||||||
|
raise InstallError("Invalid GitHub URL.")
|
||||||
|
owner, repo = parts[0], parts[1]
|
||||||
|
ref = default_ref
|
||||||
|
subpath = ""
|
||||||
|
if len(parts) > 2:
|
||||||
|
if parts[2] in ("tree", "blob"):
|
||||||
|
if len(parts) < 4:
|
||||||
|
raise InstallError("GitHub URL missing ref or path.")
|
||||||
|
ref = parts[3]
|
||||||
|
subpath = "/".join(parts[4:])
|
||||||
|
else:
|
||||||
|
subpath = "/".join(parts[2:])
|
||||||
|
return owner, repo, ref, subpath or None
|
||||||
|
|
||||||
|
|
||||||
|
def _download_repo_zip(owner: str, repo: str, ref: str, dest_dir: str) -> str:
|
||||||
|
zip_url = f"https://codeload.github.com/{owner}/{repo}/zip/{ref}"
|
||||||
|
zip_path = os.path.join(dest_dir, "repo.zip")
|
||||||
|
try:
|
||||||
|
payload = _request(zip_url)
|
||||||
|
except urllib.error.HTTPError as exc:
|
||||||
|
raise InstallError(f"Download failed: HTTP {exc.code}") from exc
|
||||||
|
with open(zip_path, "wb") as file_handle:
|
||||||
|
file_handle.write(payload)
|
||||||
|
with zipfile.ZipFile(zip_path, "r") as zip_file:
|
||||||
|
_safe_extract_zip(zip_file, dest_dir)
|
||||||
|
top_levels = {name.split("/")[0] for name in zip_file.namelist() if name}
|
||||||
|
if not top_levels:
|
||||||
|
raise InstallError("Downloaded archive was empty.")
|
||||||
|
if len(top_levels) != 1:
|
||||||
|
raise InstallError("Unexpected archive layout.")
|
||||||
|
return os.path.join(dest_dir, next(iter(top_levels)))
|
||||||
|
|
||||||
|
|
||||||
|
def _run_git(args: list[str]) -> None:
|
||||||
|
result = subprocess.run(args, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True)
|
||||||
|
if result.returncode != 0:
|
||||||
|
raise InstallError(result.stderr.strip() or "Git command failed.")
|
||||||
|
|
||||||
|
|
||||||
|
def _safe_extract_zip(zip_file: zipfile.ZipFile, dest_dir: str) -> None:
|
||||||
|
dest_root = os.path.realpath(dest_dir)
|
||||||
|
for info in zip_file.infolist():
|
||||||
|
extracted_path = os.path.realpath(os.path.join(dest_dir, info.filename))
|
||||||
|
if extracted_path == dest_root or extracted_path.startswith(dest_root + os.sep):
|
||||||
|
continue
|
||||||
|
raise InstallError("Archive contains files outside the destination.")
|
||||||
|
zip_file.extractall(dest_dir)
|
||||||
|
|
||||||
|
|
||||||
|
def _validate_relative_path(path: str) -> None:
|
||||||
|
if os.path.isabs(path) or os.path.normpath(path).startswith(".."):
|
||||||
|
raise InstallError("Skill path must be a relative path inside the repo.")
|
||||||
|
|
||||||
|
|
||||||
|
def _validate_skill_name(name: str) -> None:
|
||||||
|
altsep = os.path.altsep
|
||||||
|
if not name or os.path.sep in name or (altsep and altsep in name):
|
||||||
|
raise InstallError("Skill name must be a single path segment.")
|
||||||
|
if name in (".", ".."):
|
||||||
|
raise InstallError("Invalid skill name.")
|
||||||
|
|
||||||
|
|
||||||
|
def _git_sparse_checkout(repo_url: str, ref: str, paths: list[str], dest_dir: str) -> str:
|
||||||
|
repo_dir = os.path.join(dest_dir, "repo")
|
||||||
|
clone_cmd = [
|
||||||
|
"git",
|
||||||
|
"clone",
|
||||||
|
"--filter=blob:none",
|
||||||
|
"--depth",
|
||||||
|
"1",
|
||||||
|
"--sparse",
|
||||||
|
"--single-branch",
|
||||||
|
"--branch",
|
||||||
|
ref,
|
||||||
|
repo_url,
|
||||||
|
repo_dir,
|
||||||
|
]
|
||||||
|
try:
|
||||||
|
_run_git(clone_cmd)
|
||||||
|
except InstallError:
|
||||||
|
_run_git(
|
||||||
|
[
|
||||||
|
"git",
|
||||||
|
"clone",
|
||||||
|
"--filter=blob:none",
|
||||||
|
"--depth",
|
||||||
|
"1",
|
||||||
|
"--sparse",
|
||||||
|
"--single-branch",
|
||||||
|
repo_url,
|
||||||
|
repo_dir,
|
||||||
|
]
|
||||||
|
)
|
||||||
|
_run_git(["git", "-C", repo_dir, "sparse-checkout", "set", *paths])
|
||||||
|
_run_git(["git", "-C", repo_dir, "checkout", ref])
|
||||||
|
return repo_dir
|
||||||
|
|
||||||
|
|
||||||
|
def _validate_skill(path: str) -> None:
|
||||||
|
if not os.path.isdir(path):
|
||||||
|
raise InstallError(f"Skill path not found: {path}")
|
||||||
|
skill_md = os.path.join(path, "SKILL.md")
|
||||||
|
if not os.path.isfile(skill_md):
|
||||||
|
raise InstallError("SKILL.md not found in selected skill directory.")
|
||||||
|
|
||||||
|
|
||||||
|
def _copy_skill(src: str, dest_dir: str) -> None:
|
||||||
|
os.makedirs(os.path.dirname(dest_dir), exist_ok=True)
|
||||||
|
if os.path.exists(dest_dir):
|
||||||
|
raise InstallError(f"Destination already exists: {dest_dir}")
|
||||||
|
shutil.copytree(src, dest_dir)
|
||||||
|
|
||||||
|
|
||||||
|
def _build_repo_url(owner: str, repo: str) -> str:
|
||||||
|
return f"https://github.com/{owner}/{repo}.git"
|
||||||
|
|
||||||
|
|
||||||
|
def _build_repo_ssh(owner: str, repo: str) -> str:
|
||||||
|
return f"git@github.com:{owner}/{repo}.git"
|
||||||
|
|
||||||
|
|
||||||
|
def _prepare_repo(source: Source, method: str, tmp_dir: str) -> str:
|
||||||
|
if method in ("download", "auto"):
|
||||||
|
try:
|
||||||
|
return _download_repo_zip(source.owner, source.repo, source.ref, tmp_dir)
|
||||||
|
except InstallError as exc:
|
||||||
|
if method == "download":
|
||||||
|
raise
|
||||||
|
err_msg = str(exc)
|
||||||
|
if "HTTP 401" in err_msg or "HTTP 403" in err_msg or "HTTP 404" in err_msg:
|
||||||
|
pass
|
||||||
|
else:
|
||||||
|
raise
|
||||||
|
if method in ("git", "auto"):
|
||||||
|
repo_url = source.repo_url or _build_repo_url(source.owner, source.repo)
|
||||||
|
try:
|
||||||
|
return _git_sparse_checkout(repo_url, source.ref, source.paths, tmp_dir)
|
||||||
|
except InstallError:
|
||||||
|
repo_url = _build_repo_ssh(source.owner, source.repo)
|
||||||
|
return _git_sparse_checkout(repo_url, source.ref, source.paths, tmp_dir)
|
||||||
|
raise InstallError("Unsupported method.")
|
||||||
|
|
||||||
|
|
||||||
|
def _resolve_source(args: Args) -> Source:
|
||||||
|
if args.url:
|
||||||
|
owner, repo, ref, url_path = _parse_github_url(args.url, args.ref)
|
||||||
|
if args.path is not None:
|
||||||
|
paths = list(args.path)
|
||||||
|
elif url_path:
|
||||||
|
paths = [url_path]
|
||||||
|
else:
|
||||||
|
paths = []
|
||||||
|
if not paths:
|
||||||
|
raise InstallError("Missing --path for GitHub URL.")
|
||||||
|
return Source(owner=owner, repo=repo, ref=ref, paths=paths)
|
||||||
|
|
||||||
|
if not args.repo:
|
||||||
|
raise InstallError("Provide --repo or --url.")
|
||||||
|
if "://" in args.repo:
|
||||||
|
return _resolve_source(
|
||||||
|
Args(url=args.repo, repo=None, path=args.path, ref=args.ref)
|
||||||
|
)
|
||||||
|
|
||||||
|
repo_parts = [p for p in args.repo.split("/") if p]
|
||||||
|
if len(repo_parts) != 2:
|
||||||
|
raise InstallError("--repo must be in owner/repo format.")
|
||||||
|
if not args.path:
|
||||||
|
raise InstallError("Missing --path for --repo.")
|
||||||
|
paths = list(args.path)
|
||||||
|
return Source(
|
||||||
|
owner=repo_parts[0],
|
||||||
|
repo=repo_parts[1],
|
||||||
|
ref=args.ref,
|
||||||
|
paths=paths,
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
def _default_dest() -> str:
|
||||||
|
return os.path.join(_codex_home(), "skills")
|
||||||
|
|
||||||
|
|
||||||
|
def _parse_args(argv: list[str]) -> Args:
|
||||||
|
parser = argparse.ArgumentParser(description="Install a skill from GitHub.")
|
||||||
|
parser.add_argument("--repo", help="owner/repo")
|
||||||
|
parser.add_argument("--url", help="https://github.com/owner/repo[/tree/ref/path]")
|
||||||
|
parser.add_argument(
|
||||||
|
"--path",
|
||||||
|
nargs="+",
|
||||||
|
help="Path(s) to skill(s) inside repo",
|
||||||
|
)
|
||||||
|
parser.add_argument("--ref", default=DEFAULT_REF)
|
||||||
|
parser.add_argument("--dest", help="Destination skills directory")
|
||||||
|
parser.add_argument(
|
||||||
|
"--name", help="Destination skill name (defaults to basename of path)"
|
||||||
|
)
|
||||||
|
parser.add_argument(
|
||||||
|
"--method",
|
||||||
|
choices=["auto", "download", "git"],
|
||||||
|
default="auto",
|
||||||
|
)
|
||||||
|
return parser.parse_args(argv, namespace=Args())
|
||||||
|
|
||||||
|
|
||||||
|
def main(argv: list[str]) -> int:
|
||||||
|
args = _parse_args(argv)
|
||||||
|
try:
|
||||||
|
source = _resolve_source(args)
|
||||||
|
source.ref = source.ref or args.ref
|
||||||
|
if not source.paths:
|
||||||
|
raise InstallError("No skill paths provided.")
|
||||||
|
for path in source.paths:
|
||||||
|
_validate_relative_path(path)
|
||||||
|
dest_root = args.dest or _default_dest()
|
||||||
|
tmp_dir = tempfile.mkdtemp(prefix="skill-install-", dir=_tmp_root())
|
||||||
|
try:
|
||||||
|
repo_root = _prepare_repo(source, args.method, tmp_dir)
|
||||||
|
installed = []
|
||||||
|
for path in source.paths:
|
||||||
|
skill_name = args.name if len(source.paths) == 1 else None
|
||||||
|
skill_name = skill_name or os.path.basename(path.rstrip("/"))
|
||||||
|
_validate_skill_name(skill_name)
|
||||||
|
if not skill_name:
|
||||||
|
raise InstallError("Unable to derive skill name.")
|
||||||
|
dest_dir = os.path.join(dest_root, skill_name)
|
||||||
|
if os.path.exists(dest_dir):
|
||||||
|
raise InstallError(f"Destination already exists: {dest_dir}")
|
||||||
|
skill_src = os.path.join(repo_root, path)
|
||||||
|
_validate_skill(skill_src)
|
||||||
|
_copy_skill(skill_src, dest_dir)
|
||||||
|
installed.append((skill_name, dest_dir))
|
||||||
|
finally:
|
||||||
|
if os.path.isdir(tmp_dir):
|
||||||
|
shutil.rmtree(tmp_dir, ignore_errors=True)
|
||||||
|
for skill_name, dest_dir in installed:
|
||||||
|
print(f"Installed {skill_name} to {dest_dir}")
|
||||||
|
return 0
|
||||||
|
except InstallError as exc:
|
||||||
|
print(f"Error: {exc}", file=sys.stderr)
|
||||||
|
return 1
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
raise SystemExit(main(sys.argv[1:]))
|
||||||
107
skills/.system/skill-installer/scripts/list-skills.py
Normal file
107
skills/.system/skill-installer/scripts/list-skills.py
Normal file
@ -0,0 +1,107 @@
|
|||||||
|
#!/usr/bin/env python3
|
||||||
|
"""List skills from a GitHub repo path."""
|
||||||
|
|
||||||
|
from __future__ import annotations
|
||||||
|
|
||||||
|
import argparse
|
||||||
|
import json
|
||||||
|
import os
|
||||||
|
import sys
|
||||||
|
import urllib.error
|
||||||
|
|
||||||
|
from github_utils import github_api_contents_url, github_request
|
||||||
|
|
||||||
|
DEFAULT_REPO = "openai/skills"
|
||||||
|
DEFAULT_PATH = "skills/.curated"
|
||||||
|
DEFAULT_REF = "main"
|
||||||
|
|
||||||
|
|
||||||
|
class ListError(Exception):
|
||||||
|
pass
|
||||||
|
|
||||||
|
|
||||||
|
class Args(argparse.Namespace):
|
||||||
|
repo: str
|
||||||
|
path: str
|
||||||
|
ref: str
|
||||||
|
format: str
|
||||||
|
|
||||||
|
|
||||||
|
def _request(url: str) -> bytes:
|
||||||
|
return github_request(url, "codex-skill-list")
|
||||||
|
|
||||||
|
|
||||||
|
def _codex_home() -> str:
|
||||||
|
return os.environ.get("CODEX_HOME", os.path.expanduser("~/.codex"))
|
||||||
|
|
||||||
|
|
||||||
|
def _installed_skills() -> set[str]:
|
||||||
|
root = os.path.join(_codex_home(), "skills")
|
||||||
|
if not os.path.isdir(root):
|
||||||
|
return set()
|
||||||
|
entries = set()
|
||||||
|
for name in os.listdir(root):
|
||||||
|
path = os.path.join(root, name)
|
||||||
|
if os.path.isdir(path):
|
||||||
|
entries.add(name)
|
||||||
|
return entries
|
||||||
|
|
||||||
|
|
||||||
|
def _list_skills(repo: str, path: str, ref: str) -> list[str]:
|
||||||
|
api_url = github_api_contents_url(repo, path, ref)
|
||||||
|
try:
|
||||||
|
payload = _request(api_url)
|
||||||
|
except urllib.error.HTTPError as exc:
|
||||||
|
if exc.code == 404:
|
||||||
|
raise ListError(
|
||||||
|
"Skills path not found: "
|
||||||
|
f"https://github.com/{repo}/tree/{ref}/{path}"
|
||||||
|
) from exc
|
||||||
|
raise ListError(f"Failed to fetch skills: HTTP {exc.code}") from exc
|
||||||
|
data = json.loads(payload.decode("utf-8"))
|
||||||
|
if not isinstance(data, list):
|
||||||
|
raise ListError("Unexpected skills listing response.")
|
||||||
|
skills = [item["name"] for item in data if item.get("type") == "dir"]
|
||||||
|
return sorted(skills)
|
||||||
|
|
||||||
|
|
||||||
|
def _parse_args(argv: list[str]) -> Args:
|
||||||
|
parser = argparse.ArgumentParser(description="List skills.")
|
||||||
|
parser.add_argument("--repo", default=DEFAULT_REPO)
|
||||||
|
parser.add_argument(
|
||||||
|
"--path",
|
||||||
|
default=DEFAULT_PATH,
|
||||||
|
help="Repo path to list (default: skills/.curated)",
|
||||||
|
)
|
||||||
|
parser.add_argument("--ref", default=DEFAULT_REF)
|
||||||
|
parser.add_argument(
|
||||||
|
"--format",
|
||||||
|
choices=["text", "json"],
|
||||||
|
default="text",
|
||||||
|
help="Output format",
|
||||||
|
)
|
||||||
|
return parser.parse_args(argv, namespace=Args())
|
||||||
|
|
||||||
|
|
||||||
|
def main(argv: list[str]) -> int:
|
||||||
|
args = _parse_args(argv)
|
||||||
|
try:
|
||||||
|
skills = _list_skills(args.repo, args.path, args.ref)
|
||||||
|
installed = _installed_skills()
|
||||||
|
if args.format == "json":
|
||||||
|
payload = [
|
||||||
|
{"name": name, "installed": name in installed} for name in skills
|
||||||
|
]
|
||||||
|
print(json.dumps(payload))
|
||||||
|
else:
|
||||||
|
for idx, name in enumerate(skills, start=1):
|
||||||
|
suffix = " (already installed)" if name in installed else ""
|
||||||
|
print(f"{idx}. {name}{suffix}")
|
||||||
|
return 0
|
||||||
|
except ListError as exc:
|
||||||
|
print(f"Error: {exc}", file=sys.stderr)
|
||||||
|
return 1
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
raise SystemExit(main(sys.argv[1:]))
|
||||||
177
skills/kimi-webbridge/SKILL.md
Normal file
177
skills/kimi-webbridge/SKILL.md
Normal file
@ -0,0 +1,177 @@
|
|||||||
|
---
|
||||||
|
name: kimi-webbridge
|
||||||
|
description: |
|
||||||
|
Kimi WebBridge lets AI control the user's real browser — navigate, click, type, read, screenshot, and interact with any website using the user's actual login sessions. Use this skill whenever the user wants to interact with websites, automate browser tasks, scrape web content, or perform any action requiring a real browser. Also use when the user mentions "browser", "webpage", "open URL", "screenshot", or asks to read/interact with any website. Use even for simple-sounding browser requests — the daemon handles all complexity.
|
||||||
|
metadata:
|
||||||
|
version: "1.11.3"
|
||||||
|
---
|
||||||
|
|
||||||
|
# Kimi WebBridge
|
||||||
|
|
||||||
|
Control the user's real browser (with their login sessions) via a local daemon at `http://127.0.0.1:10086`.
|
||||||
|
|
||||||
|
## Tools
|
||||||
|
|
||||||
|
| Tool | Args | Returns | Note |
|
||||||
|
|------|------|---------|------|
|
||||||
|
| `navigate` | `url`, `newTab`(bool), `group_title` | `{success, url, tabId}` | First call opens a tab — see [Tabs](#tabs-and-the-current-tab). `group_title` sets the group's visible label |
|
||||||
|
| `find_tab` | `url`, `active`(bool) | `{success, url, tabId, borrowed}` | Re-select a tab **this session** opened; `active:true` borrows the tab the **user** is viewing — see [Tabs](#tabs-and-the-current-tab) |
|
||||||
|
| `snapshot` | — | `{url, title, tree}` with `@e` refs | **Accessibility tree** (text) — use this to read page content and locate elements |
|
||||||
|
| `click` | `selector` (@e ref or CSS) | `{success, tag, text}` | Synthetic `el.click()` |
|
||||||
|
| `fill` | `selector`, `value` | `{success, tag, mode}` | Works on `<input>`/`<textarea>` AND `[contenteditable]` (ProseMirror/Lexical/Slate). `mode` is `"value"` or `"contenteditable"` |
|
||||||
|
| `evaluate` | `code` (supports async/await) | `{type, value}` | |
|
||||||
|
| `cdp` | `method`, `params` | raw CDP response | Raw `chrome.debugger` passthrough — what `evaluate` is to JS, `cdp` is to CDP. Low-level escape hatch for cases the tools above don't cover |
|
||||||
|
| `screenshot` | `format`(png\|jpeg), `quality`(0-100), optional `selector` (@e/CSS), optional `path` | `{format, path, sizeBytes, mimeType}` | Returns a file path, not base64 — see [Screenshots](#screenshots) |
|
||||||
|
| `network` | `cmd`(start\|stop\|list\|detail), `filter`, `requestId` | request/response data | |
|
||||||
|
| `upload` | `selector`, `files`(string[]) | `{success, fileCount}` | |
|
||||||
|
| `save_as_pdf` | `paper_format`, `landscape`, `scale`, `print_background`, optional `path` | `{path, sizeBytes, mimeType, pageTitle}` | Render current page → PDF, returns a file path — see [Save as PDF](#save-the-current-page-as-pdf) |
|
||||||
|
| `list_tabs` | — | `{success, tabs:[{tabId, url, title, active, groupTitle}]}` | Inspect tabs in the current session |
|
||||||
|
| `close_tab` | — | `{success, closed: bool}` | Close the current tab in the session |
|
||||||
|
| `close_session` | — | `{success, closed: int}` | Close all tabs in the session — `closed` is the count. See [Sessions](#sessions) for when to call |
|
||||||
|
|
||||||
|
### Tabs and the current tab
|
||||||
|
|
||||||
|
Single-tab tools (`snapshot`, `click`, `fill`, `screenshot`, `save_as_pdf`) act on the **current tab** — the one you most recently opened with `navigate` or selected with `find_tab`.
|
||||||
|
|
||||||
|
- **Opening pages**: use `newTab:true` when pages should coexist (comparing, cross-referencing); omit it to send the current tab to a new URL.
|
||||||
|
- **Going back to an earlier tab**: call `find_tab` to make a tab **you opened earlier in this session** the current one again. Pass the tab's **full URL** — take it from `list_tabs` or the earlier `navigate` result. A bare root domain (`kimi.com`) may miss a `www.kimi.com` tab, so prefer the exact URL. By default `find_tab` searches **only this session's own tabs** — it never reaches into the user's other tabs or windows.
|
||||||
|
- **Acting on a page the user already has open**: pass `active:true` ("use my open X tab" / "the X page I'm viewing"). It **borrows** the tab the user is currently viewing (returns `borrowed:true`); the borrowed tab is operated in place — it is not pulled into the session's tab group.
|
||||||
|
- If `find_tab` errors with "no tab matching … in this session", the page isn't open in this session — `navigate` with `newTab:true` instead.
|
||||||
|
|
||||||
|
```bash
|
||||||
|
curl -s -X POST http://127.0.0.1:10086/command \
|
||||||
|
-d '{"action":"find_tab","args":{"url":"https://www.kimi.com","active":true},"session":"k26-research"}'
|
||||||
|
```
|
||||||
|
|
||||||
|
### Call Format
|
||||||
|
|
||||||
|
Every command carries a top-level `session` naming the current task — see [Sessions](#sessions) below. The examples in later sections omit it only for brevity; in real calls always include it. The command format depends on the user's OS.
|
||||||
|
|
||||||
|
**macOS / Linux** — inline JSON is fine:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
curl -s -X POST http://127.0.0.1:10086/command \
|
||||||
|
-H 'Content-Type: application/json' \
|
||||||
|
-d '{"action":"navigate","args":{"url":"https://example.com","newTab":true,"group_title":"My task"},"session":"my-task"}'
|
||||||
|
```
|
||||||
|
|
||||||
|
**Windows (PowerShell / cmd)** — the shell corrupts non-ASCII characters (Chinese etc.) carried inline in command arguments or pipes; they reach the daemon as `?` and the text is unrecoverable. Send **every** request as a file body instead:
|
||||||
|
|
||||||
|
1. Write the JSON body to a **uniquely-named** temp file with your own file-write tool — never with shell `echo`/heredoc, which corrupts non-ASCII the same way. Give **every** request its own filename with a random suffix (e.g. `webbridge-req-<random>.json`) so concurrent requests never share a file and overwrite each other.
|
||||||
|
2. POST the file with `curl.exe` — always `curl.exe`, never bare `curl`, which Windows PowerShell aliases to `Invoke-WebRequest`:
|
||||||
|
|
||||||
|
```powershell
|
||||||
|
curl.exe -s -X POST http://127.0.0.1:10086/command -H "Content-Type: application/json" --data-binary "@$env:TEMP\webbridge-req-<random>.json"
|
||||||
|
```
|
||||||
|
|
||||||
|
3. Delete the temp file as soon as the request returns — don't leave request bodies on disk.
|
||||||
|
|
||||||
|
## Sessions
|
||||||
|
|
||||||
|
**One task = one session = one tab group.** A `session` collects every tab the task opens into one tab group, so the user sees a single group for "what the agent is doing right now". Pass it as a **top-level field** of the request body (not inside `args`).
|
||||||
|
|
||||||
|
- **Pick one session name at the task's start, put it on every command, and never switch mid-task — even across different sites.** Switching session names per site is the #1 cause of fragmented tab groups.
|
||||||
|
- Name it after the **task**, not the site (`camping-research`, `phone-compare`). Use multiple sessions only for genuinely unrelated parallel tasks.
|
||||||
|
- `group_title` is the human-readable group label — write it in the user's language, on the **first** `navigate` of the task.
|
||||||
|
- When you create the group (the first `navigate` of a task), tell the user once that this task's pages are collected under group «title», and that you'll close them whenever they ask.
|
||||||
|
|
||||||
|
```bash
|
||||||
|
# First tab: set session + a human label (in the user's language)
|
||||||
|
curl -s -X POST http://127.0.0.1:10086/command \
|
||||||
|
-d '{"action":"navigate","args":{"url":"https://www.kimi.com","newTab":true,"group_title":"K2.6 feature research"},"session":"k26-research"}'
|
||||||
|
# Another site, same task → same session → joins the same group automatically
|
||||||
|
curl -s -X POST http://127.0.0.1:10086/command \
|
||||||
|
-d '{"action":"navigate","args":{"url":"https://www.moonshot.cn","newTab":true},"session":"k26-research"}'
|
||||||
|
```
|
||||||
|
|
||||||
|
Closing is always user-initiated: call `close_session` only when the user explicitly asks ("close those", "clear the tabs"). It clears the whole group in one call.
|
||||||
|
|
||||||
|
## Screenshots
|
||||||
|
|
||||||
|
The daemon writes the image to disk and returns `{format, path, sizeBytes, mimeType}` — never base64, since the model can't read raw image bytes. Take the `.path` and open it with the `Read` tool to actually see it.
|
||||||
|
|
||||||
|
```bash
|
||||||
|
# Default: PNG of the visible viewport, daemon picks a temp path
|
||||||
|
curl ... -d '{"action":"screenshot","args":{}}'
|
||||||
|
# Options (each independent): JPEG quality, element-only via @e/CSS selector, custom output path
|
||||||
|
curl ... -d '{"action":"screenshot","args":{"format":"jpeg","quality":60}}'
|
||||||
|
curl ... -d '{"action":"screenshot","args":{"selector":"@e123"}}'
|
||||||
|
```
|
||||||
|
|
||||||
|
A caller-supplied `path` is honored verbatim (parent dirs created, existing file overwritten) — use a unique name to avoid clobbering. `save_as_pdf` follows the same rule.
|
||||||
|
|
||||||
|
## Prefer snapshot over CSS/JS selectors
|
||||||
|
|
||||||
|
`snapshot` returns interactive elements with `@e` refs based on semantic role/name. Use them directly with click/fill — they survive CSS class hash changes that break manually-written selectors.
|
||||||
|
|
||||||
|
Fall back to `evaluate` (JS) only when:
|
||||||
|
- The target has no `@e` ref in the snapshot
|
||||||
|
- You need attributes not in the snapshot (e.g., `href`)
|
||||||
|
- You need to dispatch complex event sequences, or scroll
|
||||||
|
|
||||||
|
## Evaluate Tips
|
||||||
|
|
||||||
|
- Always use compact `JSON.stringify(data)` — never add `null, 2` formatting. Indentation and newlines can inflate the response several times over, causing truncation during transmission.
|
||||||
|
- `evaluate` calls share the page's JS realm — re-declaring the same `const`/`let` across two calls throws `SyntaxError`. Wrap in an IIFE for a fresh scope: `(() => { const x = ...; return x; })()`.
|
||||||
|
|
||||||
|
## Text input — use `fill`
|
||||||
|
|
||||||
|
`fill` (selector = CSS or `@e` ref, plus the value) works on `<input>`/`<textarea>` (returns `mode: "value"`) and on `[contenteditable]` rich editors — ProseMirror, TipTap, Lexical, Slate, Quill, etc. (returns `mode: "contenteditable"`), firing the right input events so the page reacts.
|
||||||
|
|
||||||
|
`fill` is **clear-and-insert**: existing content is replaced. To append, read the current value via `evaluate`, concatenate, then `fill` with the result.
|
||||||
|
|
||||||
|
## Form submit / special keys
|
||||||
|
|
||||||
|
There's no separate "press Enter" tool. To submit a form, click the submit button directly (`click` on the @e ref or selector). To dispatch a key event programmatically (e.g. Escape to close a modal):
|
||||||
|
|
||||||
|
```bash
|
||||||
|
{"action":"evaluate","args":{"code":"document.activeElement.dispatchEvent(new KeyboardEvent('keydown',{key:'Escape',bubbles:true}))"}}
|
||||||
|
```
|
||||||
|
|
||||||
|
## Save the current page as PDF
|
||||||
|
|
||||||
|
`save_as_pdf` renders the current page to PDF and returns the file path. All args optional:
|
||||||
|
- `paper_format`: `letter` (default) \| `a4` \| `legal` \| `a3` \| `tabloid`
|
||||||
|
- `landscape`: `false` (default)
|
||||||
|
- `scale`: `1.0` (default), range `[0.1, 2.0]`
|
||||||
|
- `print_background`: `true` (default) — keep background colors
|
||||||
|
- `path`: caller-supplied output path; if absent, daemon picks a default under OS temp dir using the page title as the filename
|
||||||
|
|
||||||
|
`path` semantics match `screenshot`: written verbatim, parent dirs auto-created, existing files overwritten.
|
||||||
|
|
||||||
|
Decoded PDF cap is 100 MB. Above that the daemon refuses; reduce `scale` or split the page.
|
||||||
|
|
||||||
|
## Known limitations
|
||||||
|
|
||||||
|
- **Sites that strictly check `event.isTrusted`** (some banking portals, captchas) ignore `click` / `fill` because those fire DOM-level synthetic events (`isTrusted=false`). For these, tell the user the page needs manual interaction. (Trusted input is possible at the protocol level via the `cdp` escape hatch, but treat that as advanced.)
|
||||||
|
- **Cross-origin iframes**: `fill`, `click`, `evaluate`, and `snapshot` operate on the top frame. If a target element lives in a same-page iframe from a different origin (e.g. embedded sandbox demos), navigate to the iframe's URL directly instead.
|
||||||
|
|
||||||
|
## If a tool call fails (daemon or extension not ready)
|
||||||
|
|
||||||
|
**If a tool call can't reach the daemon (connection refused), start it yourself — don't ask the user. This is safe to run anytime: it no-ops if the daemon is already up.**
|
||||||
|
|
||||||
|
**macOS / Linux:**
|
||||||
|
|
||||||
|
```bash
|
||||||
|
~/.kimi-webbridge/bin/kimi-webbridge start
|
||||||
|
```
|
||||||
|
|
||||||
|
**Windows (PowerShell):**
|
||||||
|
|
||||||
|
```powershell
|
||||||
|
& "$env:USERPROFILE\.kimi-webbridge\bin\kimi-webbridge.exe" start
|
||||||
|
```
|
||||||
|
|
||||||
|
Then retry the tool call. If it still fails — or the browser extension won't connect — point the user to the help page instead of deep-troubleshooting:
|
||||||
|
|
||||||
|
- English: https://www.kimi.com/features/webbridge
|
||||||
|
- 中文: https://www.kimi.com/zh-cn/features/webbridge
|
||||||
|
|
||||||
|
Never run `stop` / `restart` / `uninstall` automatically — those kill a running daemon. See `references/operations.md` for anything deeper.
|
||||||
|
|
||||||
|
## Version mismatches
|
||||||
|
|
||||||
|
If a tool returns an error containing **"Please update the Kimi WebBridge extension"**, the user's browser extension is older than this skill. Don't try to reconcile versions yourself — just tell the user, in their language, to update the extension and retry:
|
||||||
|
|
||||||
|
- English: https://www.kimi.com/features/webbridge
|
||||||
|
- 中文: https://www.kimi.com/zh-cn/features/webbridge
|
||||||
31
skills/kimi-webbridge/references/operations.md
Normal file
31
skills/kimi-webbridge/references/operations.md
Normal file
@ -0,0 +1,31 @@
|
|||||||
|
# Operations: daemon lifecycle and recovery
|
||||||
|
|
||||||
|
Read this only when a tool call can't reach the daemon, or the user explicitly asks to install / start / troubleshoot kimi-webbridge.
|
||||||
|
|
||||||
|
## The daemon
|
||||||
|
|
||||||
|
The `kimi-webbridge` binary lives at `~/.kimi-webbridge/bin/kimi-webbridge` (Windows: `%USERPROFILE%\.kimi-webbridge\bin\kimi-webbridge.exe`) and serves a local HTTP daemon on `127.0.0.1:10086`. Status, PID, and logs live under `~/.kimi-webbridge/`.
|
||||||
|
|
||||||
|
## Recovery — what to do when a tool call fails
|
||||||
|
|
||||||
|
1. **Daemon not reachable (connection refused)** → start it yourself, don't ask the user. `start` is idempotent: it no-ops if the daemon is already up, and concurrent starts converge to a single daemon (the OS lets only one process bind port 10086).
|
||||||
|
- macOS / Linux: `~/.kimi-webbridge/bin/kimi-webbridge start`
|
||||||
|
- Windows: `& "$env:USERPROFILE\.kimi-webbridge\bin\kimi-webbridge.exe" start`
|
||||||
|
|
||||||
|
Then retry the tool call.
|
||||||
|
2. **`command not found` / binary missing** → not installed. Point the user to the help page below to install it.
|
||||||
|
3. **Extension won't connect, or anything still broken after a `start` + retry** → don't deep-troubleshoot. Point the user to the help page:
|
||||||
|
- English: https://www.kimi.com/features/webbridge
|
||||||
|
- 中文: https://www.kimi.com/zh-cn/features/webbridge
|
||||||
|
|
||||||
|
## Do NOT do automatically
|
||||||
|
|
||||||
|
Never run `stop` / `restart` / `uninstall` on your own. They kill the running daemon; if the user runs the **Kimi Desktop App** (which manages its own daemon), an external stop/restart also fights the app. If a hard restart is genuinely needed, ask the user to do it themselves — reopen the Kimi Desktop App, or run `kimi-webbridge restart` by hand.
|
||||||
|
|
||||||
|
## /status JSON fields
|
||||||
|
|
||||||
|
- `running` (bool) — daemon listening on `:10086`
|
||||||
|
- `version` (string) — daemon build version
|
||||||
|
- `extension_connected` (bool) — a WebSocket client (the browser extension) is attached
|
||||||
|
- `extension_id` (string) — the Chrome/Edge extension ID, empty if none
|
||||||
|
- `uptime_seconds` (int)
|
||||||
@ -1,5 +0,0 @@
|
|||||||
def main():
|
|
||||||
print("Hello MCP!")
|
|
||||||
|
|
||||||
if __name__ == "__main__":
|
|
||||||
main()
|
|
||||||
@ -1 +0,0 @@
|
|||||||
push ok
|
|
||||||
Loading…
Reference in New Issue
Block a user