swarm은(는) 무엇을 하나요?
많은 독립적인 항목을 병렬로 처리합니다: 테이블을 만들고, 하위 에이전트로 분산한 후, 결과를 집계합니다. 각 행은 하나의 작업 단위입니다.
많은 독립적인 항목을 병렬로 처리합니다: 테이블을 만들고, 하위 에이전트로 분산한 후, 결과를 집계합니다. 각 행은 하나의 작업 단위입니다.
이 스킬은 LangChain 기반의 'Swarm' 패턴을 구현한 것으로, 대량의 독립적인 작업을 병렬로 처리해야 할 때 유용합니다. 사용자가 정의한 테이블의 각 행을 하나의 작업 단위로 삼아 다수의 하위 에이전트(subagent)에게 동시에 분배하고, 각 에이전트가 처리한 결과를 다시 집계하여 최종 응답을 제공합니다. 주로 대규모 데이터 처리, 다수 API 호출, 문서 분석 등에서 작업 속도를 획기적으로 향상시킬 수 있습니다. 이 스킬은 Claude Code, Cursor, Codex 등 다양한 AI 어시스턴트 플랫폼에서 호환되도록 설계되었으며, SKILL.md 문서를 기반으로 에이전트가 테이블 생성, 팬아웃(fan-out), 집계(aggregation)의 세 단계를 자동으로 수행합니다.
npx skills add https://github.com/langchain-ai/langchain-skills/tree/main/skills/swarmInstalled? Explore more 생산성 & 협업 skills: steipete/gemini, steipete/gh-issues, steipete/skill-creator · View all 6 →
많은 독립적인 항목을 병렬로 처리합니다: 테이블을 만들고, 하위 에이전트로 분산한 후, 결과를 집계합니다. 각 행은 하나의 작업 단위입니다.
This repo contains 11 individual skills — each has its own dedicated page.
INVOKE 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 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.
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.
Create LangChain agents with create_agent, define tools, and use middleware for human-in-the-loop and error handling.
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.
INVOKE THIS SKILL when building ANY retrieval-augmented generation (RAG) system. Covers document loaders, RecursiveCharacterTextSplitter, embeddings (OpenAI), and vector stores (Chroma, FAISS, Pinecone).
INVOKE THIS SKILL when writing ANY LangGraph code. Covers StateGraph, state schemas, nodes, edges, Command, Send, invoke, streaming, and error handling.
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.
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.
Gemini CLI one-shot prompts, summaries, generation, skills, hooks, MCP, or Gemma routing.
Fetch GitHub issues, select candidates, spawn background fix agents, open PRs, and optionally process PR review comments.
Create, edit, audit, tidy, validate, or restructure AgentSkills and SKILL.md files.
Search, install, update, sync, or publish agent skills with the ClawHub CLI and registry.
Delegate coding work to Codex, Claude Code, or OpenCode as background workers; not simple edits or read-only code lookup.
List, configure, authenticate, call, and inspect MCP servers/tools with mcporter over HTTP or stdio.