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

langgraph-docs

GitHub

获取LangGraph文档以构建状态代理、多代理工作流及人机协作模式。适用于查询LangGraph概念、API及使用指导的场景。

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

Trigger Scenarios

用户询问LangGraph相关概念或实现需要构建基于LangGraph的多代理工作流寻求LangGraph API使用指南

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/cli/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.