langgraph-docs
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.
Install
With your agent
Install OMGSkills skill "langchain-ai/deepagents:langgraph-docs" into this agent's normal skills directory: call the OMGSkills MCP get_install_plan tool for your agent and run the script it returns (it installs only the pinned commit and verifies SKILL.md), and stop if MCP or the pin is unavailable. Do not overwrite or change existing skills without asking me.
Manual command
git clone https://github.com/langchain-ai/deepagents /tmp/deepagents && ln -s /tmp/deepagents/libs/code/examples/skills/langgraph-docs ~/.claude/skills/langgraph-docsFrom 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.
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