LangChain skills collection

Deep Agents Core

Build Deep Agents applications with create_deep_agent, harness architecture, skill instructions, and configuration.

Deep Agents Memory

Configure Deep Agent memory, persistent state, and filesystem access using LangChain backends.

Deep Agents Orchestration

Coordinate Deep Agent subagents, task planning, and human approvals with SubAgentMiddleware, TodoList, and human-in-the-loop middleware.

Deepagents Python Quickstart

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

Deepagents Typescript Quickstart

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

Ecosystem Primer

Choose among LangChain, LangGraph, and Deep Agents for an agent application.

Eval Engineering

Inspect an agent repository and optional traces, interview the user, write reviewed Task Specs, build and audit Harbor tasks, and bootstrap reusable project World Knowledge Skills. Use for agent evals, benchmark design, Task generation…

Langchain Dependencies

Set up LangChain, LangGraph, and Deep Agents projects with package versions, installation guidance, and dependency management.

Langchain Fundamentals

Create LangChain agents with createagent, define tools, and use middleware for human-in-the-loop and error handling.

Langchain Middleware

Add human approvals, custom middleware, and structured output to LangChain agents.

Langchain Python Quickstart

Scaffold a minimal local LangChain agent in Python by following the official quickstart.

Langchain RAG

Build retrieval-augmented generation pipelines with document loaders, text splitting, embeddings, and vector stores.

Langchain Typescript Quickstart

Scaffold a minimal local LangChain agent in TypeScript by following the official quickstart.

Langgraph CLI

Guidance for using the langgraph CLI to scaffold, develop, build, or deploy LangGraph applications. Covers langgraph new, dev, build, up, deploy, and langgraph.json configuration.

Langgraph Decision Models

Guidance for routing a LangGraph agent with a decision model (TypeSafe Jev, SemIf) instead of an LLM, or when auditing an existing agent for LLM calls that only produce a routing decision. Covers langchain-typesafe Noul/Choice/Score…

Langgraph Fundamentals

Build LangGraph workflows with StateGraph, state schemas, nodes, edges, Command, Send, streaming, and error handling.

Langgraph Human In The Loop

Guidance for implementing human-in-the-loop patterns, pausing for approval, or handling errors in LangGraph. Covers interrupt(), Command(resume=...), approval/validation workflows, and the 4-tier error handling strategy.

Langgraph Persistence

Persist LangGraph state and conversation history, configure checkpointers, and work with historical state.

Langgraph Python Quickstart

Scaffold a minimal local LangGraph agent in Python by following the official quickstart.

Langgraph Typescript Quickstart

Scaffold a minimal local LangGraph agent in TypeScript by following the official quickstart.