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langgraph-docs

@langchain-ai Updated 2026-09-11

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.

aideepagentslangchainlanggraph

Install

git clone https://github.com/langchain-ai/deepagents /tmp/deepagents && ln -s /tmp/deepagents/libs/code/examples/skills/langgraph-docs ~/.claude/skills/langgraph-docs

From README

langgraph-docs Workflow Fetch the Documentation Index Use fetchurl to read: https://docs.langchain.com/llms.txt This returns a structured list of all available documentation with descriptions. 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 Fetch and Apply Use fetchurl on the selected URLs, then complete the user's request using the documentation content. If fetchurl fails or returns empty content, retry once. If it fails again, inform the user and suggest checking https://langchain-ai.github.io/langgraph/ directly.