How do I install the Langgraph Docs skill?

Run npx skillmds@latest add mineru98/langgraph-docs in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Langgraph Docs safe to use?

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Which AI agents work with Langgraph Docs?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Langgraph Docs free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Langgraph Docs?

Mineru98 (@mineru98) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Langgraph Docs by mineru98 — Agent Skill

Name: Langgraph Docs
Author: Mineru98

Langgraph Docs

Access up-to-date LangGraph Python documentation to provide accurate implementation guidance. Use when requests involve LangGraph concepts, APIs, or implementation questions including (1) building agents with LangGraph, (2) creating state graphs and workflows, (3) using LangGraph checkpointing and persistence, (4) implementing human-in-the-loop patterns, (5) deploying LangGraph applications, or (6) any LangGraph-specific questions requiring current documentation.

Mineru98 4fd0dae 2.5 KB Updated Sep 17, 2026 13 repo stars

File contents

LangGraph Documentation

Overview

This skill provides access to the official LangGraph Python documentation to answer questions and guide implementation with accurate, up-to-date information.

Workflow

1. Fetch the Documentation Index

Use the WebFetch tool to read the documentation index:

WebFetch with url="https://docs.langchain.com/llms.txt" and prompt="Extract the full list of documentation URLs with their descriptions"

This index provides a structured list of all available LangGraph documentation with descriptions.

2. Select Relevant Documentation

Based on the user's question, identify 2-4 most relevant documentation URLs from the index. Prioritize:

How-to guides for implementation questions (e.g., "How do I create a checkpointer?")
Concept pages for understanding questions (e.g., "What is a state graph?")
Tutorials for end-to-end examples (e.g., "Build a chatbot with LangGraph")
API reference for detailed API information (e.g., "StateGraph parameters")

3. Fetch Selected Documentation

Use the WebFetch tool to read each selected documentation URL:

WebFetch with url="[selected-doc-url]" and prompt="Extract all content including code examples, explanations, and API details"

Read 2-4 documentation pages to gather comprehensive context.

4. Provide Accurate Guidance

After reading the documentation:

Answer the user's question with information directly from the documentation
Include code examples from the documentation when relevant
Cite specific documentation URLs for reference
Recommend additional documentation pages if the user needs more context

Tips

Multiple topics: If the question spans multiple topics (e.g., "agents with persistence"), fetch documentation for each topic
Code examples: Always include working code examples from the documentation
Version compatibility: Check if the documentation mentions version-specific behavior
Related concepts: Suggest related documentation that might be helpful for the user's broader goals

---name: langgraph-docsdescription: Access up-to-date LangGraph Python documentation to provide accurate implementation guidance. Use when requests involve LangGraph concepts, APIs, or implementation questions including (1) building agents with LangGraph, (2) creating state graphs and workflows, (3) using LangGraph checkpointing and persistence, (4) implementing human-in-the-loop patterns, (5) deploying LangGraph applications, or (6) any LangGraph-specific questions requiring current documentation.---# LangGraph Documentation## OverviewThis skill provides access to the official LangGraph Python documentation to answer questions and guide implementation with accurate, up-to-date information.## Workflow### 1. Fetch the Documentation IndexUse the WebFetch tool to read the documentation index:```WebFetch with url="https://docs.langchain.com/llms.txt" and prompt="Extract the full list of documentation URLs with their descriptions"```This index provides a structured list of all available LangGraph documentation with descriptions.### 2. Select Relevant DocumentationBased on the user's question, identify 2-4 most relevant documentation URLs from the index. Prioritize:- **How-to guides** for implementation questions (e.g., "How do I create a checkpointer?")- **Concept pages** for understanding questions (e.g., "What is a state graph?")- **Tutorials** for end-to-end examples (e.g., "Build a chatbot with LangGraph")- **API reference** for detailed API information (e.g., "StateGraph parameters")### 3. Fetch Selected DocumentationUse the WebFetch tool to read each selected documentation URL:```WebFetch with url="[selected-doc-url]" and prompt="Extract all content including code examples, explanations, and API details"```Read 2-4 documentation pages to gather comprehensive context.### 4. Provide Accurate GuidanceAfter reading the documentation:- Answer the user's question with information directly from the documentation- Include code examples from the documentation when relevant- Cite specific documentation URLs for reference- Recommend additional documentation pages if the user needs more context## Tips- **Multiple topics**: If the question spans multiple topics (e.g., "agents with persistence"), fetch documentation for each topic- **Code examples**: Always include working code examples from the documentation- **Version compatibility**: Check if the documentation mentions version-specific behavior- **Related concepts**: Suggest related documentation that might be helpful for the user's broader goals

Frequently asked questions