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langgraph-docs

Fetches and references LangGraph Python documentation to build stateful agents, create multi-agent workflows, and implement human-in-the-loop patterns.

Skill by langchain-aiOfficial

IndexedMIT★ 30,550
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/langchain-ai-langgraph-docs

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About

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.

Use cases: backend, agent-building, documentation, agent-orchestration

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
No tools found
Secrets
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Install scripts
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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/langgraph-docs

What's inside

Skill name
langgraph-docs
Description
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.
License
MIT
Instructions
25 lines in SKILL.md · view on GitHub

Files (1)

  • SKILL.md

SKILL.md (first lines)

# 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.

From langchain-ai/deepagents, MIT.

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Stars
30,550
Forks
4,302
Open issues
163
Last commit (this folder)
May 12, 2026 (5 months ago)
Last release
Oct 23, 2026 (7 days ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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langgraph-docs skill. Agent Mart. https://agentmart.dev/skills/langchain-ai-langgraph-docs (last updated 2026-10-24)