langgraph-docs
This skill explains how to access LangGraph Python documentation to help answer questions and guide implementation, ensuring users can effectively utilize LangGraph.
npx skills add langchain-ai/deepagents --skill langgraph-docsBefore / After Comparison
1 组Searching for LangGraph documentation is time-consuming and laborious, making it difficult to quickly locate needed information. Encountering difficulties during implementation, there's a lack of immediate guidance, affecting development progress.
The skill directly accesses LangGraph documentation, providing instant answers to questions. It offers implementation guidance, ensuring users efficiently utilize LangGraph and accelerates project development.
langgraph-docs
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:
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Implementation questions — specific how-to guides
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Conceptual questions — core concept pages
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End-to-end examples — tutorials
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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.
Weekly Installs2.0KRepositorylangchain-ai/deepagentsGitHub Stars14.3KFirst SeenJan 22, 2026Security AuditsGen Agent Trust HubPassSocketPassSnykWarnInstalled onopencode1.8Kcodex1.4Kgemini-cli1.3Kgithub-copilot1.3Kkimi-cli1.2Kamp1.2K
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