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EdgeOne Makers CLI command reference. Use when running edgeone CLI commands for dev, build, deploy, env management.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
| name | makers-cli |
| description | EdgeOne Makers CLI command reference. Use when running edgeone CLI commands for dev, build, deploy, env management. |
| metadata | {"author":"edgeone","version":"1.0.0"} |
npm install -g edgeone
Verify: edgeone -v
| Command | Description |
|---|---|
edgeone makers dev | Start local dev server (agent runtime + frontend) |
edgeone makers build | Build agents + frontend into .edgeone/ |
edgeone makers deploy | Build and deploy to EdgeOne Makers |
edgeone makers deploy -n <name> | Deploy as a new project |
edgeone makers deploy -t <token> | Deploy with API token (CI/headless) |
edgeone makers deploy -e preview | Deploy to preview environment |
edgeone makers link | Link local project to remote EdgeOne project |
edgeone makers env pull | Pull remote env vars to local .env |
edgeone makers env set <KEY> <VALUE> | Set a remote environment variable |
edgeone makers env ls | List remote environment variables |
edgeone makers env rm <KEY> | Remove a remote environment variable |
edgeone login | Login (browser-based) |
edgeone login --site china | Login to China site |
edgeone login --site global | Login to Global site |
edgeone whoami | Check current login status |
Before any edgeone command, set:
export PAGES_SOURCE=skills
Or inline: PAGES_SOURCE=skills edgeone makers dev
npm install -g edgeone
edgeone login
PAGES_SOURCE=skills edgeone makers link
PAGES_SOURCE=skills edgeone makers env pull
PAGES_SOURCE=skills edgeone makers dev
edgeone makers deploy
edgeone makers env set WSA_API_KEY "your-key"
edgeone makers env set SUPABASE_URL "https://xxx.supabase.co"
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.
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.