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Official agent skill

Deepagents Python Quickstart

by langchain-ai in langchain-ai/langchain-skills

Scaffold a minimal local Deep Agent in Python by following the official quickstart, using provider-native web search instead of Tavily.

OfficialMITAuto-check: notesProductivity & Automation

Install Deepagents Python Quickstart

skills CLI
$ npx skills add langchain-ai/langchain-skills --skill deepagents-python-quickstart -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install langchain-ai/langchain-skills deepagents-python-quickstart --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/langchain-ai/langchain-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/config/skills/deepagents-python-quickstart .claude/skills/deepagents-python-quickstart && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
deepagents-python-quickstart
GitHub stars
1.3k
Token cost
~549 tokens
SKILL.md length
237 words
Files
1
Skills in repo
22
Repo updated
First seen
Licence
MIT

At a glance

Scaffold a minimal local Deep Agent in Python by following the official quickstart, using provider-native web search instead of Tavily.

  • Works in 5 steps: Ask which provider/model to use.… → Create a new directory (e.g.… → Do not use Tavily (or any second search… → …
  • The user wants to quickly build
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Try a Deep Agent locally

What it does

Deepagents Python Quickstart is an agent skill from langchain-ai/langchain-skills, published by the product's own GitHub organization. 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.

Its SKILL.md is about 550 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Productivity & Automation, covering Web search. It works with Python, Tavily, LangChain and LangGraph. The licence is MIT.

When your agent uses it

  • The user wants to quickly build
  • Try a Deep Agent locally

Example prompts

  • “/deepagents-python-quickstart”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Ask which provider/model to use. Showcase that Deep Agents are model-agnostic. Suggested prompt
  2. Create a new directory (e.g. deep-agent/) and do all work there — do not pollute the open project.
  3. Do not use Tavily (or any second search vendor). Replace the quickstart's internet_search / Tavily tool with the chosen provider's…
  4. Install deepagents (+ python-dotenv) and the provider package for their model — not tavily-python.
  5. Run the research example, show output, then stop. Point to deep-agents-core / customization / Managed Deep Agents for next steps.

What it can do on your machine

Read from SKILL.md and the folder at commit 16a992f. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • docs.langchain.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Deepagents Python Quickstart loads about 549 tokens when it runs. Until then it costs about 59 tokens; SKILL.md has 237 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~59
When it runs · the whole SKILL.md, loaded when a task matches
~549

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NoteMentions a .env fileSKILL.md:33
    Only secret: that provider's API key in `.env` (gitignored). Skip LangSmith tracing unless they ask.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from langchain-ai/langchain-skills at commit 16a992f, republished under its MIT licence (© langchain-ai). 237 words, ~549 tokens.

Download SKILL.mdSave it as .claude/skills/deepagents-python-quickstart/SKILL.md (or your agent's skills folder).
name
deepagents-python-quickstart
description
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.

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):

  1. 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).

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

  3. 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):

    ProviderBuilt-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.

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

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

© langchain-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in config/skills/deepagents-python-quickstart of langchain-ai/langchain-skills.

Open the folder on GitHubat commit 16a992f

Compare with similar skills

Deepagents Python Quickstart next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Deepagents Python Quickstart compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Deepagents Python Quickstart this skilllangchain-ai/langchain-skills1.3k—~549Automated safety check: NotesMIT
Ag2 Use Builtin Toolsag2ai/build-with-ag2252—~1.3kAutomated safety check: PassApache-2.0
Add Example AgentGetBindu/Bindu10k—~1.1kAutomated safety check: NotesCustom licence
Tool Designagentailor/fullstack-langgraph-nextjs-agent132—~3.2kAutomated safety check: PassMIT
Deepagents Setup Configurationsoba-labs/langchain-agent-skills107—~1.9kAutomated safety check: PassMIT
Langgraph Testing Evaluationsoba-labs/langchain-agent-skills107—~2.3kAutomated safety check: PassMIT

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Works with

Categories

Questions about Deepagents Python Quickstart

What does Deepagents Python Quickstart do?

Scaffold a minimal local Deep Agent in Python by following the official quickstart, using provider-native web search instead of Tavily. Deepagents Python Quickstart is an agent skill from langchain-ai/langchain-skills, published by the product's own GitHub organization. Scaffold a minimal local Deep Agent in Python by following the official quickstart, using provider-native web search instead of Tavily.

When should I use Deepagents Python Quickstart?

Deepagents Python Quickstart fits situations like: the user wants to quickly build; try a Deep Agent locally.

How do I install Deepagents Python Quickstart in Claude Code?

Run `npx skills add langchain-ai/langchain-skills --skill deepagents-python-quickstart -a claude-code`. Or copy the skill folder (config/skills/deepagents-python-quickstart in langchain-ai/langchain-skills) into .claude/skills/deepagents-python-quickstart in your project. Claude Code loads it when a task matches its description.

How do I install Deepagents Python Quickstart in Codex?

Run `npx skills add langchain-ai/langchain-skills --skill deepagents-python-quickstart -a codex`. Or copy the skill folder (config/skills/deepagents-python-quickstart in langchain-ai/langchain-skills) into .agents/skills/deepagents-python-quickstart in your project. Codex loads it when a task matches its description.

Can I use Deepagents Python Quickstart in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add langchain-ai/langchain-skills --skill deepagents-python-quickstart -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/deepagents-python-quickstart, .gemini/skills/deepagents-python-quickstart, .github/skills/deepagents-python-quickstart and .opencode/skills/deepagents-python-quickstart in your project.

What does Deepagents Python Quickstart need to run?

SKILL.md names no scripts, command-line tools or credentials: Deepagents Python Quickstart is instructions for the agent only. Our summary lists: Python 3.

Does Deepagents Python Quickstart access the network?

SKILL.md names 1 domain. As links in the text: docs.langchain.com. This is read from the text; nothing was executed.

Is Deepagents Python Quickstart safe to install?

Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Deepagents Python Quickstart use?

Deepagents Python Quickstart is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Deepagents Python Quickstart use?

About 549 tokens (SKILL.md is roughly 2.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Deepagents Python Quickstart?

Skills that share tags, products or a category with Deepagents Python Quickstart: Ag2 Use Builtin Tools (ag2ai/build-with-ag2, 252 stars), Add Example Agent (GetBindu/Bindu, 10k stars), Tool Design (agentailor/fullstack-langgraph-nextjs-agent, 132 stars) and Deepagents Setup Configuration (soba-labs/langchain-agent-skills, 107 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Deepagents Python Quickstart?

langchain-ai (a GitHub organization, an official publisher) maintains it in langchain-ai/langchain-skills, which has 1,270 GitHub stars. The repository holds 22 skills in this directory. The repository was last updated on October 5, 2026.

Source: langchain-ai/langchain-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.