Deepagents Python Quickstart Skill for Claude

Scaffold a minimal local Deep Agent in Python by following the official quickstart, using provider-native web search instead of Tavily. Use when the user wants to quickly build or try a Deep Agent locally.

552 tokens

context cost

the whole folder, loaded on every use

files

instructions only

copies elsewhere

how many repositories repackaged it

1080

stars on the repo

on the repository, not the skill itself

Install

one command, takes just this skill from the repository

npx skills add https://github.com/langchain-ai/langchain-skills --skill deepagents-python-quickstart

The instruction itself

2 sections, as written by the author

Deep Agents Python quickstart

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

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

Fetch that page (Docs MCP or HTTP) and implement the research-agent shape it shows (create_deep_agent, research system prompt, invoke with a research question like “What is LangGraph?”).

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 Deep Agents are 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-3.5-flash. Default if you're unsure: anthropic:claude-sonnet-5.

> We'll use that provider's built-in web search (no separate search API key).

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

Do not use Tavily (or any second search vendor). Replace the quickstart's internet_search / Tavily tool with the chosen provider's built-in web search. Look up the current tool shape on that provider's LangChain chat docs (examples as of writing — re-check if needed):

| Provider | Built-in search tool |

|----------|----------------------|

| Anthropic | {"type": "web_search_20260209", "name": "web_search", "max_uses": 5} |

| OpenAI | {"type": "web_search"} |

| Google | {"google_search": {}} |

Prefer Anthropic / OpenAI / Google so provider search is available. Only secret: that provider's API key in .env (gitignored). Skip LangSmith tracing unless they ask.

Install deepagents (+ python-dotenv) and the provider package for their model — not tavily-python.

Run the research example, show output, then stop. Point to deep-agents-core / customization / Managed Deep Agents for next steps.

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How to use it

Copy the folder

Take langchain-ai/deepagents-python-quickstart from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.