Agent Skills › langchain-ai/langchain-skills › langchain-typescript-quickstart

langchain-typescript-quickstart

GitHub

基于 LangChain 官方文档，引导用户在本地 TypeScript 环境中快速搭建最小化 Agent。通过询问模型提供商、配置环境变量及安装依赖，实现模型无关的 Agent 示例运行，适用于快速原型验证或学习入门。

config/skills/langchain-typescript-quickstart/SKILL.md langchain-ai/langchain-skills

Trigger Scenarios

用户希望快速构建或尝试 LangChain Agent 需要基于官方文档初始化 TypeScript 项目

Install

npx skills add langchain-ai/langchain-skills --skill langchain-typescript-quickstart -g -y

More Options

Non-standard path

npx skills add https://github.com/langchain-ai/langchain-skills/tree/main/config/skills/langchain-typescript-quickstart -g -y

Use without installing

npx skills use langchain-ai/langchain-skills@langchain-typescript-quickstart

指定 Agent (Claude Code)

npx skills add langchain-ai/langchain-skills --skill langchain-typescript-quickstart -a claude-code -g -y

安装 repo 全部 skill

npx skills add langchain-ai/langchain-skills --all -g -y

预览 repo 内 skill

npx skills add langchain-ai/langchain-skills --list

SKILL.md

Frontmatter

{
    "name": "langchain-typescript-quickstart",
    "description": "Scaffold a minimal local LangChain agent in TypeScript by following the official quickstart. Use when the user wants to quickly build or try a LangChain agent locally."
}

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 a provider:model string — 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 .env themselves — 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-fundamentals for next steps.