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EdgeOne Makers Full-Stack Development Tools

Development Updated 2026.08.30

Paste the following prompt into your AI chat to install this skill:

Please install @user_cdc69ff0/edgeone-makers-tools according to https://skillhub.cn/install/skillhub.md.

About this skill

Problem Context

Building on EdgeOne Makers often involves more than one API: AI agent frameworks, cloud function runtimes, edge function constraints, KV/Blob storage, middleware routing, and deployment. Reading all docs at once can pollute context with unrelated details, while guessing interfaces from experience can miss platform conventions and project structure.

How It Works

The skill splits EdgeOne Makers development references into task-specific SKILL.md files. For a given task, it loads only the matching module:
- AI Agent development: DeepAgents, LangGraph, Claude SDK, OpenAI Agents, and CrewAI.
- Deploy: project deployment to EdgeOne.
- Edge Functions and Cloud Functions: V8 lightweight functions versus Node.js/Go/Python APIs.
- KV + Blob Storage, Middleware, CLI, Recipes, and Environment adaptation: storage, auth/rewrites/routing, command reference, scaffolding, and WorkBuddy/sandbox/CI differences.

Scope and Notes

It is best used to help coding assistants retrieve precise context for a single task rather than replacing the full platform documentation. If a task spans multiple modules, read the relevant skills separately instead of loading everything at once.

Use Cases

  • Build an AI Agent with LangGraph in EdgeOne Makers and configure KV storage for session state.
  • Turn a Node.js API into a Cloud Function and add authentication and routing middleware.
  • Handle edge requests with a V8 Edge Function, then deploy the project to EdgeOne.
  • Adapt project scaffolding in WorkBuddy, sandbox, or CI and run EdgeOne deployment commands.

Best For

  • Engineers maintaining EdgeOne Makers apps who need task-specific function, storage, and middleware references.
  • Backend developers building AI agents who need to integrate LangGraph or CrewAI and deploy on the platform.
  • DevOps engineers owning release workflows who need to handle WorkBuddy, sandbox, and CI differences.
  • Full-stack developers writing edge or cloud functions who need to distinguish V8 Edge Functions from Node, Go, and Python APIs.