Agent Skillslangchain-ai/langchain-skills › langchain-python-quickstart

langchain-python-quickstart

GitHub

指导用户基于官方文档在本地快速搭建最小化 LangChain Agent,支持模型无关配置与隔离环境。

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

Trigger Scenarios

用户希望快速体验或构建 LangChain Agent 需要本地初始化 LangChain 开发环境

Install

npx skills add langchain-ai/langchain-skills --skill langchain-python-quickstart -g -y
More Options

Non-standard path

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

Use without installing

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

指定 Agent (Claude Code)

npx skills add langchain-ai/langchain-skills --skill langchain-python-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-python-quickstart",
    "description": "Scaffold a minimal local LangChain agent in Python by following the official quickstart. Use when the user wants to quickly build or try a LangChain agent locally."
}

LangChain Python quickstart

Follow the live docs — do not invent an alternate API from memory:

https://docs.langchain.com/oss/python/langchain/quickstart

Fetch that page (Docs MCP or HTTP) and implement what it shows (weather agent + create_agent).

Local setup constraints

Apply these on top of the quickstart (they keep setup minimal and model-agnostic):

  1. 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).

  2. Create a new directory (e.g. langchain-agent/) and do all work there — do not pollute the open project.

  3. 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.

  4. Install the provider package needed for their model if the quickstart's base install isn't enough.

  5. Run the example, show output, then stop. Point to langchain-fundamentals for next steps.

Version History

  • f3ea282 Current 2026-08-02 21:50

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Metadata

Files
0
Version
b7a2a8f
Hash
06176156
Indexed
2026-08-02 21:50

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