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.
Source facts
- Repository
- langchain-ai/deepagents
- Last source activity
- May 12, 2026 at 17:39
- Detected SKILL.md language
- English
- Stars
- 30,321
- Forks
- 4,263
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Source instructions · Read-only preview- 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.
# 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.
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