Access LangGraph documentation to build stateful agents and multi-agent workflows.
Automate repetitive workflows and reduce manual effort
Example: Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example: Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example: Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Time estimate: 15-45 minutes depending on use case complexity
Prerequisites
Submit your Claude Code skill and start earning
epx add langchain-ai/deepagents --skill langgraph-docsCompatible with
Supported agents
Fetches official LangGraph Python docs covering state machines, graph-based agent design, and human-in-the-loop patterns
Prioritizes relevant documentation by query type: implementation guides for how-to questions, concept pages for theory, tutorials for end-to-end examples, and API references for technical details
Automatically selects 2–4 most relevant documentation URLs and retrieves their content t
22:T48c,<h1>langgraph-docs</h1>
<h2>Workflow</h2> <h3>1. Fetch the Documentation Index</h3> <p>Use <code>fetch_url</code> to read: <a href="https://docs.langchain.com/llms.txt" target="_blank" rel="ugc nofollow noopener">https://docs.langchain.com/llms.txt</a></p> <p>This returns a structured list of all available documentation with descriptions.</p> <h3>2. Select Relevant Documentation</h3> <p>Identify 2-4 most relevant URLs from the index. Prioritize:</p> <ul> <li><strong>Implementation questions</strong> — specific how-to guides</li> <li><strong>Conceptual questions</strong> — core concept pages</li> <li><strong>End-to-end examples</strong> — tutorials</li> <li><strong>API details</strong> — reference docs</li> </ul> <h3>3. Fetch and Apply</h3> <p>Use <code>fetch_url</code> on the selected URLs, then complete the user's request using the documentation content.</p> <p>If <code>fetch_url</code> fails or returns empty content, retry once. If it fails again, inform the user and suggest checking <a href="https://langchain-ai.github.io/langgraph/" target="_blank" rel="ugc nofollow noopener">https://langchain-ai.github.io/langgraph/</a> directly.</p>1d:["$","div",null,{"className":"prose prose-invert max-w-none prose-headings:font-semibold prose-headings:tracking-tight prose-h1:text-4xl prose-h1:mb-2 prose-h2:text-2xl prose-h2:mb-2 prose-h3:text-lg prose-h3:mb-2 prose-p:text-muted-foreground prose-li:text-muted-foreground prose-code:bg-muted prose-code:text-foreground prose-code:px-1 prose-code:py-0.5 prose-code:rounded-sm prose-code:text-sm prose-code:before:content-none prose-code:after:content-none prose-pre:bg-muted prose-pre:text-foreground prose-pre:border prose-pre:border-border prose-pre:rounded-md [&_table]:!border-[color:var(--border)] [&_th]:!border-[color:var(--border)] [&_td]:!border-[color:var(--border)]","dangerouslySetInnerHTML":{"__html":"$22"}}] 18:[["$","meta","0",{"charSet":"utf-8"}],["$","meta","1",{"name":"viewport","content":"width=device-width, initial-scale=1"}]] 16:nullAI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionlanggraph-docsExecute the skills CLI command in your project's root directory to begin installation:
epx add langchain-ai/deepagents --skill langgraph-docsFetches langgraph-docs from langchain-ai/deepagents and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
.cursor/skills/langgraph-docs
Restart Cursor to activate langgraph-docs. Access via /langgraph-docsin your agent's command palette.
Learn more:View source on GitHubSkills CLI docsAbout CursorWhat are agent skills?
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
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langgraph-docs fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
langgraph-docs is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Useful defaults in langgraph-docs — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
langgraph-docs has been reliable in day-to-day use. Documentation quality is above average for community skills.
I recommend langgraph-docs for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
langgraph-docs is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
langgraph-docs is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
We added langgraph-docs from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: langgraph-docs is focused, and the summary matches what you get after install.
Keeps context tight: langgraph-docs is the kind of skill you can hand to a new teammate without a long onboarding doc.
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