¿Qué hace deep-agents-orchestration?
INVOCA ESTA HABILIDAD cuando uses subagentes, planificación de tareas o aprobación humana en Deep Agents. Cubre SubAgentMiddleware, TodoList para planificación e interrupciones HITL (Human-In-The-Loop).
INVOCA ESTA HABILIDAD cuando uses subagentes, planificación de tareas o aprobación humana en Deep Agents. Cubre SubAgentMiddleware, TodoList para planificación e interrupciones HITL.
Esta habilidad, langchain-ai/deep-agents-orchestration, es esencial para desarrolladores que trabajan con el framework Deep Agents. Proporciona las herramientas y patrones necesarios para orquestar flujos de agentes complejos, incluyendo la gestión de subagentes, la planificación de tareas mediante TodoList y la implementación de puntos de control de aprobación humana (HITL, por sus siglas en inglés). Es útil porque permite diseñar sistemas multiagente robustos y controlados, donde las tareas se descomponen, asignan a subagentes especializados y se supervisan mediante interrupciones humanas cuando es necesario. La habilidad se basa en componentes como SubAgentMiddleware para la comunicación entre agentes, TodoList para la planificación estructurada y los mecanismos de interrupción HITL para garantizar la seguridad y el control de calidad. Soporta el ecosistema Deep Agents y se invoca mediante el comando de habilidad correspondiente en el archivo SKILL.md.
npx skills add https://github.com/langchain-ai/langchain-skills/tree/main/skills/deep-agents-orchestrationInstalled? Explore more Productividad y colaboración skills: steipete/gemini, steipete/gh-issues, steipete/skill-creator · View all 6 →
INVOCA ESTA HABILIDAD cuando uses subagentes, planificación de tareas o aprobación humana en Deep Agents. Cubre SubAgentMiddleware, TodoList para planificación e interrupciones HITL (Human-In-The-Loop).
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 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.
Dispatches many independent items in parallel: create a table, fan out to subagents, aggregate results. One row = one unit of work.
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.