Official agent skill

Deep Agents

Build batteries-included agents with planning, context management, subagent delegation, and sandboxed execution.

OfficialMITAuto-check passedAgent Workflows

Install Deep Agents

skills CLI

$ npx skills add langchain-ai/docs --skill deep-agents -a claude-code

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

GitHub CLI

$ gh skill install langchain-ai/docs deep-agents --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/docs.git skills-src && mkdir -p .claude/skills && cp -r skills-src/src/.mintlify/skills/deep-agents .claude/skills/deep-agents && 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/

Paste into Claude Code

Install the "deep-agents" agent skill from https://github.com/langchain-ai/docs/tree/main/src/.mintlify/skills/deep-agents into .claude/skills/deep-agents/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deep-agents", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/langchain-ai/docs/tree/main/src/.mintlify/skills/deep-agents

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add langchain-ai/docs --skill deep-agents -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install langchain-ai/docs deep-agents --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/langchain-ai/docs.git skills-src && mkdir -p .agents/skills && cp -r skills-src/src/.mintlify/skills/deep-agents .agents/skills/deep-agents && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "deep-agents" agent skill from https://github.com/langchain-ai/docs/tree/main/src/.mintlify/skills/deep-agents into .agents/skills/deep-agents/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deep-agents", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add langchain-ai/docs --skill deep-agents -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install langchain-ai/docs deep-agents --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/langchain-ai/docs.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/src/.mintlify/skills/deep-agents .cursor/skills/deep-agents && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "deep-agents" agent skill from https://github.com/langchain-ai/docs/tree/main/src/.mintlify/skills/deep-agents into .cursor/skills/deep-agents/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deep-agents", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/langchain-ai/docs.git --path src/.mintlify/skills/deep-agents

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add langchain-ai/docs --skill deep-agents -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install langchain-ai/docs deep-agents --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/langchain-ai/docs.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/src/.mintlify/skills/deep-agents .gemini/skills/deep-agents && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "deep-agents" agent skill from https://github.com/langchain-ai/docs/tree/main/src/.mintlify/skills/deep-agents into .gemini/skills/deep-agents/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deep-agents", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install langchain-ai/docs deep-agents

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add langchain-ai/docs --skill deep-agents -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/langchain-ai/docs.git skills-src && mkdir -p .github/skills && cp -r skills-src/src/.mintlify/skills/deep-agents .github/skills/deep-agents && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "deep-agents" agent skill from https://github.com/langchain-ai/docs/tree/main/src/.mintlify/skills/deep-agents into .github/skills/deep-agents/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deep-agents", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add langchain-ai/docs --skill deep-agents -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install langchain-ai/docs deep-agents --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/langchain-ai/docs.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/src/.mintlify/skills/deep-agents .opencode/skills/deep-agents && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "deep-agents" agent skill from https://github.com/langchain-ai/docs/tree/main/src/.mintlify/skills/deep-agents into .opencode/skills/deep-agents/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deep-agents", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: deep-agents
GitHub stars: 426
Token cost: ~1.1k tokens
SKILL.md length: 299 words
Files: 1
Skills in repo: 17
Repo updated: Oct 9, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Build batteries-included agents with planning, context management, subagent delegation, and sandboxed execution.

Multi-step tasks that need built-in capabilities
SKILL.md covers When to use, When NOT to use, Install and Quick reference, plus 3 more sections
Calls pip and npm; reaches reference.langchain.com
Tasks that involve Context engineering

What it does

Deep Agents is an agent skill from langchain-ai/docs, published by the product's own GitHub organization. Build batteries-included agents with planning, context management, subagent delegation, and sandboxed execution. Use for complex, multi-step tasks that need built-in capabilities.

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts. Compatibility notes: Python 3.10+, Node.js 22+. Requires a model that supports tool calling.

It sits in Agent Workflows, covering Context engineering, Subagents and Building AI agents. It works with LangChain and LangGraph. The repository describes itself as: Unified LangChain documentation. The licence is MIT.

When your agent uses it

Multi-step tasks that need built-in capabilities
Tasks that involve Context engineering
Tasks that involve Subagents

Example prompts

“/deep-agents”

Requirements

Python 3
Node.js
Compatibility (from SKILL.md): Python 3.10+, Node.js 22+. Requires a model that supports tool calling.

What it can do on your machine

Read from SKILL.md and the folder at commit be3028f. 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
Shell commands in SKILL.md call:
- pip
- npm
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
- reference.langchain.com
Also links to:
- 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.
Compatibility
Python 3.10+, Node.js 22+. Requires a model that supports tool calling.
From compatibility in the SKILL.md frontmatter.

Context cost

Deep Agents loads about 1.1k tokens when it runs. Until then it costs about 48 tokens; SKILL.md has 299 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~48
When it runs · the whole SKILL.md, loaded when a task matches: ~1.1k

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 passed

The automated check found no risky patterns in SKILL.md.

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/docs at commit be3028f, republished under its MIT licence (© langchain-ai). 299 words, ~1,066 tokens.

Download SKILL.mdSave it as .claude/skills/deep-agents/SKILL.md (or your agent's skills folder).

name: deep-agents
description: Build batteries-included agents with planning, context management, subagent delegation, and sandboxed execution. Use for complex, multi-step tasks that need built-in capabilities.
compatibility: Python 3.10+, Node.js 22+. Requires a model that supports tool calling.
license: MIT
metadata.author: langchain-ai
metadata.version: 1.0

Deep Agents

Deep Agents is the easiest way to start building agents powered by LLMs—with built-in capabilities for task planning, file systems for context management, subagent delegation, and long-term memory. It is an "agent harness" built on LangChain core building blocks and the LangGraph runtime.

When to use

Use Deep Agents when you need to:

Build agents fast with sensible defaults and minimal configuration
Handle complex, multi-step tasks that benefit from automatic planning
Manage context with a built-in virtual filesystem for large inputs
Delegate subtasks to specialized subagents
Run code safely in sandboxed execution environments
Use a terminal agent via Deep Agents Code

When NOT to use

For simple tool-calling agents without planning or subagents, use LangChain agents instead—lighter weight
For custom graph-based orchestration with explicit control flow, use LangGraph directly
Deep Agents is the highest-level abstraction—it trades flexibility for convenience

Install

bash

# Python
pip install deepagents

# JavaScript/TypeScript
npm install deepagents langchain @langchain/core

Quick reference

Create a deep agent

python

# pip install deepagents langchain-anthropic
from deepagents import create_deep_agent

def get_weather(city: str) -> str:
    """Get weather for a given city."""
    return f"It's always sunny in {city}!"

agent = create_deep_agent(
    model="anthropic:claude-sonnet-4-6",
    tools=[get_weather],
    system_prompt="You are a helpful assistant",
)

result = agent.invoke(
    {"messages": [{"role": "user", "content": "What is the weather in SF?"}]}
)

Use Deep Agents Code

bash

# Install Deep Agents Code
pip install deepagents-code

# Run an interactive terminal agent
deepagents

Built-in capabilities

Capability	Description
Planning	Automatic task decomposition for complex requests
File system	Virtual filesystem for reading, writing, and managing context
Subagents	Spawn child agents for parallel subtask execution
Context management	Automatic context compression for long conversations
Sandboxed execution	Run code in isolated environments (Modal, Runloop, Daytona)
Protocols	ACP, MCP, and A2A support for interoperability

Key documentation

Overview—What Deep Agents is and how it compares to LangChain and LangGraph
Quickstart—Build your first deep agent
Customization—Configure models, tools, and behavior
Context engineering—Manage context for complex tasks
Subagents—Delegate work to child agents
Sandboxes—Run code in isolated environments
Code—Deep Agents Code, the terminal agent interface
Deploy—Deploy to production

API reference

For SDK class and method details, use the LangChain API Reference site:

MCP server: https://reference.langchain.com/mcp

langchain—Core building blocks that Deep Agents is built on
langgraph—Runtime that powers Deep Agents' durable execution
langsmith—Trace, evaluate, and deploy your deep agents

Files

Just SKILL.md in src/.mintlify/skills/deep-agents of langchain-ai/docs.

Open the folder on GitHubat commit be3028f

Compare with similar skills

Deep Agents 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.

Deep Agents compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Deep Agents this skilllangchain-ai/docs	426	—	~1.1k	Automated safety check: Pass	MIT	today
Deep Agents Corelangchain-ai/langchain-skills	1.3k	—	~3.1k	Automated safety check: Pass	MIT	today
Langchain Deep Agentsjeremylongshore/tons-of-skills-marketplace	2.8k	—	~4.9k	Automated safety check: Pass	MIT	today
Magic ResumeMagic-Resume/Magic-Resume	101	—	~663	Automated safety check: Pass	MIT	4 days ago
Mem0 Platform SDKmem0ai/mem0	67k	1 repos	~2.2k	Automated safety check: Pass	Apache-2.0	today
Pydantic AI Harnesspydantic/pydantic-ai	20k	—	~4.9k	Automated safety check: Pass	MIT	today

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More from langchain-ai/docs

All 17 skills in this repo

Add Docs Page
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Add, move, rename, or delete a page on the LangChain docs site.
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Docs Code Samples
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A skill your agent uses when migrating inline code samples from LangChain docs (MDX files) into external, testable code files that are extracted by this repo’s snippet scripts and used as Mintlify…
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Docs Edit
langchain-ai/docs
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Edit a docs page that already has an open pull request, or revise a page in place.
426 GitHub stars~1.9k tokensUpdated today
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Docs Restructure
langchain-ai/docs
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Restructure documentation that spans several pages. An agent skill from langchain-ai/docs.
426 GitHub stars~1.7k tokensUpdated today
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Docs Team Voice
langchain-ai/docs
Official
Write or revise documentation prose so it reads like the rest of this site, in the docs team's shared voice.
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Langchain
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Build agents with a prebuilt architecture and integrations for any model or tool.
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Works with

Questions about Deep Agents

What does Deep Agents do?

Build batteries-included agents with planning, context management, subagent delegation, and sandboxed execution. Deep Agents is an agent skill from langchain-ai/docs, published by the product's own GitHub organization. Build batteries-included agents with planning, context management, subagent delegation, and sandboxed execution.

When should I use Deep Agents?

Deep Agents fits situations like: multi-step tasks that need built-in capabilities; tasks that involve Context engineering; tasks that involve Subagents.

How do I install Deep Agents in Claude Code?

Run `npx skills add langchain-ai/docs --skill deep-agents -a claude-code`. Or copy the skill folder (src/.mintlify/skills/deep-agents in langchain-ai/docs) into .claude/skills/deep-agents in your project. Claude Code loads it when a task matches its description.

How do I install Deep Agents in Codex?

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

Can I use Deep Agents 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/docs --skill deep-agents -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/deep-agents, .gemini/skills/deep-agents, .github/skills/deep-agents and .opencode/skills/deep-agents in your project.

What does Deep Agents need to run?

Going by SKILL.md and its folder, Deep Agents needs the command-line tools its instructions call (pip and npm). Our summary lists: Python 3; Node.js. Compatibility (from SKILL.md): Python 3.10+, Node.js 22+. Requires a model that supports tool calling..

Does Deep Agents access the network?

SKILL.md names 2 domains. In commands or code: reference.langchain.com; the agent is likely to contact it when it follows the instructions. As links in the text: docs.langchain.com. This is read from the text; nothing was executed.

Is Deep Agents safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Deep Agents use?

Deep Agents is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Deep Agents use?

About 1.1k tokens (SKILL.md is roughly 4.3k 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 Deep Agents?

Skills that share tags, products or a category with Deep Agents: Deep Agents Core (langchain-ai/langchain-skills, 1.3k stars), Langchain Deep Agents (jeremylongshore/tons-of-skills-marketplace, 2.8k stars), Magic Resume (Magic-Resume/Magic-Resume, 101 stars) and Mem0 Platform SDK (mem0ai/mem0, 67k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Deep Agents?

langchain-ai (a GitHub organization, an official publisher) maintains it in langchain-ai/docs, which has 426 GitHub stars. The repository holds 17 skills in this directory. The repository was last updated on October 9, 2026.

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

Install Deep Agents

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Compatibility

Context cost

Safety

SKILL.md

Deep Agents

When to use

When NOT to use

Install

Quick reference

Create a deep agent

Use Deep Agents Code

Built-in capabilities

Key documentation

API reference

Related skills

Files

Compare with similar skills

Similar skills

More from langchain-ai/docs

Related

Questions about Deep Agents