Agent Skills › langchain-ai/deepagents › langgraph-docs

langgraph-docs

GitHub

该技能用于获取LangGraph官方文档，辅助构建有状态智能体、多智能体工作流及人机协作模式。当用户咨询LangGraph相关问题或需要实现指导时触发，通过检索并应用文档内容解决需求。

libs/code/examples/skills/langgraph-docs/SKILL.md langchain-ai/deepagents

Trigger Scenarios

用户询问LangGraph使用方法需要构建图智能体或状态机请求多智能体工作流实现指导涉及LangGraph API细节查询

Install

npx skills add langchain-ai/deepagents --skill langgraph-docs -g -y

More Options

Non-standard path

npx skills add https://github.com/langchain-ai/deepagents/tree/main/libs/code/examples/skills/langgraph-docs -g -y

Use without installing

npx skills use langchain-ai/deepagents@langgraph-docs

指定 Agent (Claude Code)

npx skills add langchain-ai/deepagents --skill langgraph-docs -a claude-code -g -y

安装 repo 全部 skill

npx skills add langchain-ai/deepagents --all -g -y

预览 repo 内 skill

npx skills add langchain-ai/deepagents --list

SKILL.md

Frontmatter

{
    "name": "langgraph-docs",
    "description": "Fetches and references LangGraph Python documentation to build stateful agents, create multi-agent workflows, and implement human-in-the-loop patterns. Use when the user asks about LangGraph, graph agents, state machines, agent orchestration, LangGraph API, or needs LangGraph implementation guidance."
}

langgraph-docs

Workflow

1. Fetch the Documentation Index

Use fetch_url to read: https://docs.langchain.com/llms.txt

This returns a structured list of all available documentation with descriptions.

2. Select Relevant Documentation

Identify 2-4 most relevant URLs from the index. Prioritize:

Implementation questions — specific how-to guides
Conceptual questions — core concept pages
End-to-end examples — tutorials
API details — reference docs

3. Fetch and Apply

Use fetch_url on the selected URLs, then complete the user's request using the documentation content.

If fetch_url fails or returns empty content, retry once. If it fails again, inform the user and suggest checking https://langchain-ai.github.io/langgraph/ directly.