How to use
- Copy the installation command and review the source package before installing it in your own agent environment.
- Check the source document for required tools, credentials and supported hosts.
- Describe your input and desired deliverable; review the output against the source material.
npx skills add https://github.com/langchain-ai/langchain-skills --skill langchain-typescript-quickstartBefore you start
- Installation does not include a model subscription, API allowance or permission to access your files.
- Repository stars and installation counts describe activity, not an independent quality or security test.
Original skill document
Rendered from the source repository. Headings, examples, code, tables, links, and referenced images are preserved.
LangChain TypeScript quickstart
Follow the live docs — do not invent an alternate API from memory:
https://docs.langchain.com/oss/javascript/langchain/quickstart
Fetch that page (Docs MCP or HTTP) and implement what it shows (weather agent + createAgent). Requires Node 22+.
Local setup constraints
Apply these on top of the quickstart (they keep setup minimal and model-agnostic):
- Ask which provider/model to use. Showcase that LangChain is model-agnostic. Suggested prompt:
Which model should this agent use? Pass aprovider:modelstring — e.g.openai:gpt-5.5,anthropic:claude-sonnet-5,google-genai:gemini-2.5-flash-lite. Default if you're unsure: `anthropic:claude-sonnet-5`.
Swap the quickstart's model string for their choice (or the default).
- Create a new directory (e.g.
langchain-agent/) and do all work there — do not pollute the open project.
- Only secret: the provider API key in
.env(gitignored). No LangSmith / Tavily unless they ask. Prefer they edit.envthemselves — don't paste keys into chat.
- Install the provider package needed for their model if the quickstart's base install isn't enough.
- Run the example, show output, then stop. Point to
langchain-fundamentalsfor next steps.
