Langgraph Docs

by langchain-ai6a3a12bc5b3aNo license30K starsListed Oct 8, 2026Updated Oct 8, 2026Repository updated today

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.

AI-generated overview

Fetches LangGraph Python documentation to guide building stateful agents, multi-agent workflows and human-in-the-loop patterns.

What it does
This skill directs the agent to fetch the LangGraph documentation index, pick the two to four most relevant pages for the user's question, and then fetch those pages. It uses the retrieved documentation to answer implementation, conceptual, tutorial or API questions about LangGraph. If fetching fails, it retries once and then points the user to the public LangGraph site.
When to use it
Use it when a user asks about LangGraph, graph agents, state machines, agent orchestration or the LangGraph API. It also fits requests needing LangGraph implementation guidance.
Requirements
Requires a fetch_url tool with network access to the LangGraph documentation site. Ships no scripts; instructions only.

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.

Source and attribution

Source:langchain-ai/deepagentsinlibs/code/examples/skills/langgraph-docsat commit6a3a12b

License: No license

Content belongs to its original authors. SourceWeft indexes it from a public repository.

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