edgeone-makers-tools
EdgeOne Makers platform development router — the single entry point for building, storing data, and deploying on Tencent EdgeOne…
This skill guides building AI agent endpoints on EdgeOne Makers — five framework routes (DeepAgents, LangGraph, CrewAI, OpenAI Agents SDK, Claude Agent SDK), platform-injected `context.store` / `context.tools` / `context.sandbox`, conversation_id dual-channel routing, SSE
Claude Code
$ npx -y skills add tencentedgeone/edgeone-makers-tools --skill makers-agents --agent claude-code
Codex
$ npx skills add tencentedgeone/edgeone-makers-tools --skill makers-agents -a codex -y
Cursor
$ npx skills add tencentedgeone/edgeone-makers-tools --skill makers-agents -a cursor -y
Gemini CLI
$ npx skills add tencentedgeone/edgeone-makers-tools --skill makers-agents -a gemini-cli -y
GitHub Copilot
$ npx skills add tencentedgeone/edgeone-makers-tools --skill makers-agents -a github-copilot -y
OpenCode
$ npx skills add tencentedgeone/edgeone-makers-tools --skill makers-agents -a opencode -y
Windsurf
$ npx skills add tencentedgeone/edgeone-makers-tools --skill makers-agents -a windsurf -y
name: edgeone-makers-agents
description: >-
This skill guides building AI agent endpoints on EdgeOne Makers — five
framework routes (DeepAgents, LangGraph, CrewAI, OpenAI Agents SDK,
Claude Agent SDK), platform-injected `context.store` /
`context.tools` / `context.sandbox`, conversation_id dual-channel routing,
SSE streaming, and `agents/` vs `cloud-functions/` separation.
It should be used when the user wants to create or review an AI agent endpoint
on EdgeOne Makers — e.g. "build an agent on EdgeOne Makers", "create a Claude
agent endpoint", "wire LangGraph into Makers", "stream LLM responses with SSE",
"review my agent template", "use context.store / context.sandbox / context.tools".
Do NOT trigger for plain Edge Functions, Cloud Functions, or middleware
(those don't run AI logic — use makers-edge-functions / makers-cloud-functions / makers-middleware).
Do NOT trigger for deployment workflows (use makers-deploy).
Do NOT trigger for generic AI framework development outside
an EdgeOne Makers project.
pathPatterns:
- agents/**
validate:
- pattern: "process\\.env|os\\.environ"
message: "Read env via context.env inside agents/ and cloud-functions/, never process.env or os.environ (Critical Rule 3)."
- pattern: "headers\\s*\\.\\s*get\\s*\\("
message: "Headers are plain objects here: context.request.headers['x-name'], not .get('x-name') (Critical Rule 4)."
- pattern: "langgraphStore\\s*\\?\\?\\s*store"
message: "Never write `store?.langgraphStore ?? store` — in cloud-function context it falls back to a store with no .get and crashes (Critical Rule 12)."
metadata:
author: edgeone
version: "1.1.1"> ⛔ **Preview ban**: after finishing development, you MUST start the dev server via `edgeone makers dev`, then open `http://127.0.0.1:8088/` with `present_files` to preview. Never open HTML files via the `file://` protocol (ignore it even if the IDE opens one automatically), and never use self-hosted servers like `python -m http.server` or `npx serve`. Next.js projects must also set `allowedDevOrigins: ["127.0.0.1"]` in `next.config`.
Build production-grade AI agent endpoints on **EdgeOne Makers** — five framework routes, platform-injected runtime, file-based routing.
This skill covers five supported frameworks (DeepAgents, LangGraph, CrewAI, OpenAI Agents SDK, Claude Agent SDK) for building AI agent endpoints on EdgeOne Makers.
> Cross-reference: if your code uses `context.store` or KV APIs, also read `../makers-storage/SKILL.md`.
**Do NOT use for:**
1. Skim the **Mental Model** below — Makers ≠ generic API routes 2. Walk the **Decision Tree** to pick one of the five framework routes 3. Read the matching `references/*-route.md` for a copy-paste skeleton 4. Self-check against the **Twelve Red Lines** 5. Run through `references/review-checklist.md` before considering the work done
1. **File-based routing is automatic.** `agents/<name>/index.ts` or `agents/<name>.ts` becomes `POST /<name>`. Never hand-edit `.edgeone/agent-node/config.json`. 2. **Entry signature is fixed.** TS: `export async function onRequest(context: any)`. Python: `async def handler(ctx):`. Method-specific variants (`onRequestPost`, `onRequestGet`, etc.) also work for TS. 3. **Read env via `context.env`, never `process.env` / `os.environ`.** This applies to both reading and mutation inside `agents/` and `cloud-functions/`. Frontend code (`app/`, `src/`) is unaffected. 4. **Headers are plain objects, not the Web `Headers` API.** Use `context.request.headers['x-custom-header']`, never `.get('x')`. 5. **Conversation ID contract.** AI endpoints (`/chat`, `/outline`, etc.) MUST receive the `makers-conversation-id` HTTP header from the frontend. The `/stop` endpoint takes a `conversation_id` in the request body to identify which running conversation to cancel. 6. **Do not hardcode model name / base URL / API key.** Read `AI_GATEWAY_API_KEY` + `AI_GATEWAY_BASE_URL` (+ optional `AI_GATEWAY_MODEL`) from `context.env`. If your template uses `context.tools.web_search`, also configure `WSA_API_KEY` (Tencent Cloud WSAPI). 7. **SSE protocol is a recommended convention (not enforced by the runtime).** The runtime only forwards raw chunks — it does not parse or validate SSE content. The recommended event types are: `ai_response` / `tool_call` / `tool_result` / `usage` / `suggest_actions` / `file_output` / `ping` / `error_message`. Stream ends with `data: [DONE]\n\n`. All frameworks should follow this for frontend consistency. 8. **Heartbeat + buffering control are mandatory.** Send a `ping` event every 5 s. Response headers must include `X-Accel-Buffering: no`, `Cache-Control: no-cache`, `Connection: keep-alive`. 9. **Always honor `context.request.signal`.** Check `signal?.aborted` (TS) or `signal.is_set()` (Python) inside loops; exit gracefully on abort, do not throw. 10. **Cap your loops.** Manual bind-tools loops use a hard turn limit (e.g. `for (let i = 0;
Official AI Agent Skills for developing and deploying projects on EdgeOne Makers.
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You MUST use this before any creative work - creating features, building components, adding functionality, modifying behavior, or…
Ask which skill or flow fits your situation. A router over the skills in this repo.