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By langchain-ai
Build and orchestrate AI agents using LangChain, LangGraph, and Deep Agents — scaffold, develop, deploy, and manage stateful agent workflows with memory, RAG pipelines, human-in-the-loop approval, and parallel task execution.
npx claudepluginhub langchain-ai/langchain-skills --plugin langchain-skillsINVOKE THIS SKILL when building ANY Deep Agents application. Covers create_deep_agent(), harness architecture, SKILL.md format, and configuration options.
INVOKE THIS SKILL when your Deep Agent needs memory, persistence, or filesystem access. Covers StateBackend (ephemeral), StoreBackend (persistent), FilesystemMiddleware, and CompositeBackend for routing.
INVOKE THIS SKILL when using subagents, task planning, or human approval in Deep Agents. Covers SubAgentMiddleware, TodoList for planning, and HITL interrupts.
INVOKE 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 patterns, install, environment setup, and which skill to load next.
INVOKE THIS SKILL when setting up a new project or when asked about package versions, installation, or dependency management for LangChain, LangGraph, LangSmith, or Deep Agents. Covers required packages, minimum versions, environment requirements, versioning best practices, and common community tool packages for both Python and TypeScript.
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Sign in to claimBased on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
Editorial "Agent Architect" bundle for Claude Code from Antigravity Awesome Skills.
LLM application development with LangGraph, RAG systems, vector search, and AI agent architectures for Claude 4.6 and GPT-5.4
Expert LangGraph/LangChain agent builder with MCP integration, workflow orchestration, and CLI accessibility. Creates production-ready AI agents that are reachable via command line and Claude Code.
LangChain JS/TS development - agents, chains, LangGraph workflows, and Deep Agents patterns
Design patterns for the Langroid multi-agent LLM framework
shareAI Lab's skills for AI agents - knowledge packages that extend agent capabilities
LangSmith skills for tracing, dataset management, and evaluation pipelines
Traces Claude Code conversations to LangSmith, including subagent and tool executions
⚠️ — This project is in early development. APIs and skill content may change.
Agent skills for building agents with LangChain, LangGraph, and Deep Agents.
Want your agent to self-improve? Use langsmith-skills to observe, evaluate, and iterate on your LLM applications.
These skills can be installed via npx skills for any agent that supports the Agent Skills specification, including Claude Code, Cursor, Windsurf, and more.
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 (e.g. Claude Code):
npx skills add langchain-ai/langchain-skills --agent claude-code --skill '*' --yes --global
Install directly as a Claude Code plugin:
/plugin marketplace add langchain-ai/langchain-skills
/plugin install langchain-skills@langchain-skills
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 |
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).
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