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langchain-ai/deep-agents-core

Deep Agents 애플리케이션을 구축할 때 이 스킬을 호출하세요. create_deep_agent(), 하네스 아키텍처, SKILL.md 형식, 구성 옵션을 다룹니다.

deep-agents-core란 무엇인가요?

이 스킬은 langchain-ai/deep-agents-core 패키지를 사용하여 Deep Agents 애플리케이션을 구축하는 데 필요한 핵심 지식을 제공합니다. 개발자는 create_deep_agent() 함수를 통해 에이전트를 생성하고, 하네스 아키텍처를 이해하여 에이전트의 실행 환경을 구성할 수 있습니다. 또한 SKILL.md 형식에 따라 스킬 문서를 작성하는 방법과 다양한 구성 옵션을 활용하는 방법을 배울 수 있습니다. 주로 Claude Code, Cursor, Codex와 같은 AI 에이전트 플랫폼에서 사용되며, 복잡한 에이전트 기반 워크플로우를 효율적으로 설계하고 배포하는 데 유용합니다.

지원 대상✓Claude Code~Codex CLI~Cursor
npx skills add https://github.com/langchain-ai/langchain-skills/tree/main/skills/deep-agents-core

Installed? Explore more 생산성 & 협업 skills: steipete/gemini, steipete/gh-issues, steipete/skill-creator · View all 6 →

즐겨 사용하는 AI에게 물어보기

이 에이전트 스킬이 미리 로드된 새 채팅을 엽니다.

문서

deep-agents-core은(는) 무엇을 하나요?

이 스킬을 호출하세요: Deep Agents 애플리케이션을 구축할 때. create_deep_agent(), 하네스 아키텍처, SKILL.md 형식, 구성 옵션을 다룹니다.

Individual skills in this repo

This repo contains 11 individual skills — each has its own dedicated page.

langchain-ai/deep-agents-memory

INVOKE THIS SKILL when your Deep Agent needs memory, persistence, or filesystem access. Covers StateBackend (ephemeral), StoreBackend (persistent), FilesystemMiddleware, and CompositeBackend for routing.

langchain-ai/deep-agents-orchestration

INVOKE THIS SKILL when using subagents, task planning, or human approval in Deep Agents. Covers SubAgentMiddleware, TodoList for planning, and HITL interrupts.

langchain-ai/framework-selection

INVOKE THIS SKILL at the START of any LangChain/LangGraph/Deep Agents project, before writing any agent code. Determines which framework layer is right for the task: LangChain, LangGraph, Deep Agents, or a combination. Must be consulted before other agent skills.

langchain-ai/langchain-dependencies

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.

langchain-ai/langchain-fundamentals

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

langchain-ai/langchain-middleware

INVOKE THIS SKILL when you need human-in-the-loop approval, custom middleware, or structured output. Covers HumanInTheLoopMiddleware for human approval of dangerous tool calls, creating custom middleware with hooks, Command resume patterns, and structured output with Pydantic/Zod.

langchain-ai/langchain-rag

INVOKE THIS SKILL when building ANY retrieval-augmented generation (RAG) system. Covers document loaders, RecursiveCharacterTextSplitter, embeddings (OpenAI), and vector stores (Chroma, FAISS, Pinecone).

langchain-ai/langgraph-fundamentals

INVOKE THIS SKILL when writing ANY LangGraph code. Covers StateGraph, state schemas, nodes, edges, Command, Send, invoke, streaming, and error handling.

langchain-ai/langgraph-human-in-the-loop

INVOKE THIS SKILL when 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.

langchain-ai/langgraph-persistence

INVOKE THIS SKILL when your LangGraph needs to persist state, remember conversations, travel through history, or configure subgraph checkpointer scoping. Covers checkpointers, thread_id, time travel, Store, and subgraph persistence modes.

langchain-ai/swarm

Dispatches many independent items in parallel: create a table, fan out to subagents, aggregate results. One row = one unit of work.

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