# 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. Use when this capability is needed. - Skill: `tomevault-io/langgraph-docs` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/langgraph-docs` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/langgraph-docs/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/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: - **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. --- > Converted and distributed by [TomeVault](https://tomevault.io/claim/langchain-ai) — claim your Tome and manage your conversions.