Build production LangChain agents with create_agent(), tools, and middleware patterns.
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/langchain-skills --skill langchain-fundamentalsCompatible with
Supported agents
Use create_agent() with model, tools list, and system prompt; configure state persistence with checkpointer and thread_id for conversation memory across invocations
Define tools via @tool decorator (Python) or tool() function (TypeScript) with clear descriptions so agents know when to call them
Add middleware like HumanInTheLoopMiddleware for approval workflows, custom error handling, and human-in-
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AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionlangchain-fundamentalsExecute the skills CLI command in your project's root directory to begin installation:
epx add langchain-ai/langchain-skills --skill langchain-fundamentalsFetches langchain-fundamentals from langchain-ai/langchain-skills 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/langchain-fundamentals
Restart Cursor to activate langchain-fundamentals. Access via /langchain-fundamentalsin 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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Registry listing for langchain-fundamentals matched our evaluation — installs cleanly and behaves as described in the markdown.
I recommend langchain-fundamentals for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Solid pick for teams standardizing on skills: langchain-fundamentals is focused, and the summary matches what you get after install.
langchain-fundamentals reduced setup friction for our internal harness; good balance of opinion and flexibility.
langchain-fundamentals fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
langchain-fundamentals has been reliable in day-to-day use. Documentation quality is above average for community skills.
langchain-fundamentals is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
langchain-fundamentals has been reliable in day-to-day use. Documentation quality is above average for community skills.
langchain-fundamentals fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
langchain-fundamentals has been reliable in day-to-day use. Documentation quality is above average for community skills.
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