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edgeone-makers-tools
edgeone-makers-tools contiene 10 skills recopiladas de TencentEdgeOne, con cobertura ocupacional por repositorio y páginas de detalle dentro del sitio.
Skills en este repositorio
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 edgeone-pages-dev instead). Do NOT trigger for deployment workflows (use edgeone-pages-deploy). Do NOT trigger for generic AI framework development outside an EdgeOne Makers project.
EdgeOne Makers CLI command reference. Use when running edgeone CLI commands for dev, build, deploy, env management.
Migrate existing AI agent projects (LangChain, LangGraph, OpenAI Agents SDK, Claude Agent SDK, CrewAI) to EdgeOne Makers platform conventions. Use when the user wants to adapt a standard agent project to run on EdgeOne Makers, convert Express/Next.js API routes to Makers handlers, or add platform capabilities (context.tools, context.sandbox, context.store). Do NOT trigger for new agent projects (use makers-agents instead).
V8-based lightweight edge functions on EdgeOne Makers. Covers routing, KV storage access, request/response handling, and environment variables at the edge.
Edge middleware for EdgeOne Makers — request interception, redirects, rewrites, auth guards, A/B testing, and header injection at the edge (V8 runtime).
Environment-specific adaptation rules for EdgeOne Makers Skills running in sandboxed or restricted AI coding environments (e.g. WorkBuddy). Trigger when: the user is working in WorkBuddy, a sandboxed IDE, or any non-interactive/CI environment where CLI commands may hang or network is isolated. Covers: non-interactive CLI flags, network isolation workarounds, login in sandbox, proxy bypass, file preview constraints (MUST use http:// via dev server, NEVER file://, NEVER python -m http.server / npx serve), dev server requirements.
Project structure templates and scaffolding recipes for typical EdgeOne Makers applications — full-stack apps, static sites, API services, and AI agent projects.
KV and Blob storage services on EdgeOne Makers. KV for edge key-value pairs, Blob for file/object storage in Cloud Functions. Covers SDK usage, setup, and troubleshooting.
EdgeOne Makers Cloud Functions — Node.js, Go, and Python runtimes. Use when building server-side APIs, Express/Koa patterns, or backend logic.
This skill deploys frontend and full-stack projects to EdgeOne Makers (Tencent EdgeOne). Trigger this skill whenever deployment is part of the task — whether as the primary intent or a secondary step. Examples: "deploy my app", "publish this site", "push this live", "create a preview deployment", "deploy to EdgeOne", "ship to production", "go live", "release", "publish a new version", "redeploy", "上线", "发布", "发一版", "重新部署", "搭建并部署", "开发并上线", "build and deploy", "create and deploy". ⚠️ Also trigger when any agent is about to execute `edgeone makers deploy` or `edgeone makers deploy` commands — the skill contains critical rules for parsing deploy output and presenting access URLs. Do NOT trigger for post-deployment runtime errors (e.g. CORS issues, 500 errors after deploy — use edgeone-makers-dev for troubleshooting).