deepagents
Gives you a ready-made agent for long, multi-step coding work that can delegate subtasks to sub-agents, manage its own context, keep memory across sessions, and ask you to approve tool calls before they run.
2 skills2 MCP31k
@langchain-aiDevelopment
langchain-skills
Agent skills for building agents with LangChain, LangGraph, and Deep Agents. Covers Deep Agents setup, memory and filesystem backends, subagents, task planning, and human-in-the-loop approval.
Plugin Signal84/100Strong
maintained100
capable65
documented100
adopted66
Auto-invoked ships a router so the right skill fires automatically as you prompt. No remembering which skill to call.
Normal is the plain upstream plugin, installed as-is. You invoke its skills yourself.
Claude Code
The plugin> /plugin marketplace add langchain-ai/langchain-skills> /plugin install langchain-skills@langchain-skillsAuto-invocation> /plugin marketplace add flowy-sh/flowy-core> /plugin install flowy-core> /plugin install flowy-langchain-skills
Codex
$ npx skills add langchain-ai/langchain-skills -a codex
Cursor
$ npx skills add langchain-ai/langchain-skills -a cursor
Gemini CLI
$ npx skills add langchain-ai/langchain-skills -a gemini-cli
GitHub Copilot
$ copilot plugin marketplace add langchain-ai/langchain-skills$ copilot plugin install langchain-skills@langchain-skills
OpenCode
$ npx skills add langchain-ai/langchain-skills -a opencode
Windsurf
$ npx skills add langchain-ai/langchain-skills -a windsurf
Stats
1,340
Stars
111
Forks
Active
Maintenance
TypeScript
Language
MIT
License
Last commit
Created
In this plugin
- deep-agents-core
- deep-agents-memory
- deep-agents-orchestration
- deepagents-python-quickstart
- deepagents-typescript-quickstart
- ecosystem-primer
- eval-engineering
- langchain-dependencies
- langchain-fundamentals
- langchain-middleware
- langchain-python-quickstart
- langchain-rag
- langchain-typescript-quickstart
- langgraph-cli
- langgraph-decision-models
- langgraph-fundamentals
- langgraph-human-in-the-loop
- langgraph-persistence
- langgraph-python-quickstart
- langgraph-typescript-quickstart
- managed-deep-agents
- swarm
What's inside
22 Skills
/deep-agents-coreINVOKE THIS SKILL when building ANY Deep Agents application. Covers create_deep_agent(), harness architecture, SKILL.md format, and configuration options./deep-agents-memoryINVOKE THIS SKILL when your Deep Agent needs memory, persistence, or filesystem access. Covers StateBackend (ephemeral), StoreBackend (persistent), FilesystemMiddleware, and CompositeBackend for routing./deep-agents-orchestrationINVOKE THIS SKILL when using subagents, task planning, or human approval in Deep Agents. Covers SubAgentMiddleware, TodoList for planning, and HITL interrupts./deepagents-python-quickstartScaffold 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./deepagents-typescript-quickstartScaffold a minimal local Deep Agent in TypeScript 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./ecosystem-primerINVOKE FIRST for any LangChain / LangGraph / Deep Agents agent building project before consulting other skills or writing any agent code. Required starting point for up to date info on framework selection (LangChain vs LangGraph vs Deep Agents vs hybrid composition), agent
- /eval-engineering
- /langchain-dependencies
- /langchain-fundamentals
- /langchain-middleware
- /langchain-python-quickstart
- /langchain-rag
- /langchain-typescript-quickstart
- /langgraph-cli
- /langgraph-decision-models
- /langgraph-fundamentals
- /langgraph-human-in-the-loop
- /langgraph-persistence
- /langgraph-python-quickstart
- /langgraph-typescript-quickstart
- /managed-deep-agents
- /swarm
README
LangChain Skills
⚠️ — This project is in early development. APIs and skill content may change.
Agent skills for building agents with LangChain, LangGraph, and Deep Agents.
For LangSmith-specific trace and dataset workflows, use langsmith-skills.
Supported Coding Agents
These skills can be installed via npx skills for any agent that supports the Agent Skills specification, including Claude Code, Cursor, Windsurf, and more.
Installation
Quick Install
Using npx skills:
Local (current project):
npx skills add langchain-ai/langchain-skills --skill '*' --yes
Global (all projects):
npx skills add langchain-ai/langchain-skills --skill '*' --yes --global
To link skills to a specific agent:
# Claude Code
npx skills add langchain-ai/langchain-skills --agent claude-code --skill '*' --yes --global
# Codex
npx skills add langchain-ai/langchain-skills --agent codex --skill '*' --yes --global
# GitHub Copilot (including Copilot in VS Code)
npx skills add langchain-ai/langchain-skills --agent github-copilot --skill '*' --yes --global
Codex also supports installing repository-hosted skills with its built-in skill installer; see the official Codex skills documentation.
Claude Code Plugin
Install directly as a Claude Code plugin:
/plugin marketplace add langchain-ai/langchain-skills
/plugin install langchain-skills@langchain-skills
Install Script (Claude Code & Deep Agents CLI only)
Alternatively, clone the repo and use the install script:
# Install for Claude Code in current directory (default)
./install.sh
# Install for Claude Code in a specific project directory
./install.sh ~/my-project
# Install for Claude Code globally
./install.sh --global
# Install for Deep Agents CLI in a specific project directory
./install.sh --deepagents ~/my-project
# Install for Deep Agents CLI globally (includes agent persona)
./install.sh --deepagents --global
| Flag / Argument | Description |
|---|---|
DIRECTORY | Target project directory (default: current directory, ignored with --global) |
--claude | Install for Claude Code (default) |
--deepagents | Install for Deep Agents CLI |
--global, -g | Install globally instead of current directory |
--force, -f | Overwrite skills with same names as this package |
--yes, -y | Skip confirmation prompts |
Usage
After installation, set your API keys:
export OPENAI_API_KEY=<your-key> # For OpenAI models
export ANTHROPIC_API_KEY=<your-key> # For Anthropic models
Then run your coding agent from the directory where you installed (for local installs) or from anywhere (for global installs).
Eval Engineering
To install only the eval-engineering skill:
npx skills add langchain-ai/langchain-skills --skill eval-engineering --yes
Or ask Codex: “Install the eval-engineering skill from langchain-ai/langchain-skills.”
Eval tasks require Harbor. Run Harbor locally with Docker or use a supported cloud environment.
Then ask your coding agent:
Use the eval-engineering skill to create a new eval Task for this project. Review the current repository and existing evals. Traces for this agent can be found here [optional Tracing Project/Location].
Available Skills (21)
Getting Started
- ecosystem-primer - Start-here primer: framework selection (LangChain vs LangGraph vs Deep Agents), env setup, and which skill to load next
- langchain-dependencies - Full package version and dependency management reference (Python + TypeScript)
Quickstarts (local)
Thin wrappers around the official Mintlify quickstarts — ask for provider/model (default anthropic:claude-sonnet-5), new directory, provider API key only:
- langchain-python-quickstart / langchain-typescript-quickstart → Python / JS (weather)
- langgraph-python-quickstart / langgraph-typescript-quickstart → Python / JS (math)
- deepagents-python-quickstart / deepagents-typescript-quickstart → Python / JS (research; provider web search instead of Tavily)
Deep Agents
- deep-agents-core - Agent architecture, harness setup, and SKILL.md format
- deep-agents-memory - Memory, persistence, filesystem middleware
- deep-agents-orchestration - Subagents, task planning, human-in-the-loop
- managed-deep-agents - Managed Deep Agents: deploy with the CLI, use the SDKs, stream runs, connect MCP tools, and build React
useStreamUIs
LangChain
- langchain-fundamentals - Agents with create_agent, tools, structured output, middleware basics
- langchain-middleware - Human-in-the-loop approval, custom middleware, Command resume patterns
- langchain-rag - RAG pipeline (document loaders, embeddings, vector stores)
LangGraph
- langgraph-fundamentals - StateGraph, nodes, edges, state reducers
- langgraph-persistence - Checkpointers, thread_id, cross-thread memory
- langgraph-cli - CLI lifecycle: scaffold, dev, build, deploy, langgraph.json config
- langgraph-human-in-the-loop - Interrupts, human review, approval workflows
Evaluation
- eval-engineering - Design and audit Harbor Tasks while building reusable project World knowledge with human review
Utilities
- swarm - Dispatch independent work items in parallel and aggregate the results
Stars on GitHub
Momentum
- stars in total
- 1.3k
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@facebookQuestions about langchain-skills.
Install it once and the right skill fires as you prompt, with no slash command to remember. It is listed on Flowy in the Development category. It includes deep-agents-core, deep-agents-memory, deep-agents-orchestration. Free and open source.
- What is langchain-skills?
- langchain-ai/langchain-skills is a plugin of skills and agents for building agents with LangChain, LangGraph, and Deep Agents. It covers Deep Agents setup, memory, subagent orchestration, and quickstarts. It is in early development, so APIs may change.
- How do I install langchain-skills?
- Run these in Claude Code: /plugin marketplace add langchain-ai/langchain-skills then /plugin install langchain-skills@langchain-skills. Then prompt normally.
- Does langchain-skills auto-invoke its skills?
- Yes. It ships a FLOW.md router that Flowy's hook fires, so the matching skill runs as you prompt. You never name a skill.
- Is langchain-skills free?
- Yes. Flowy is free and open source, with nothing gated. You can read every skill in full before you install.
- Which coding agents can use langchain-skills's skills?
- langchain-skills installs in Claude Code, and its skills also install in Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI. Each skill's page has the install command. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.
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