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Found 13 Skills
Transform Claude Code into a fully autonomous agent system with persistent memory, scheduled operations, computer use, and task queuing. Replaces standalone agent frameworks (Hermes, AutoGPT) by leveraging Claude Code's native crons, dispatch, MCP tools, and memory. Use when the user wants continuous autonomous operation, scheduled tasks, or a self-directing agent loop.
Builds LLM applications with LangChain including chains, agents, memory, tools, and RAG pipelines. Use when users request "LangChain setup", "LLM chain", "AI workflow", "conversational AI", or "RAG pipeline".
Multi-agent adversarial verification with convergence loop. Two independent review agents must both pass before output ships.
Look up VoltAgent documentation embedded in node_modules/@voltagent/core/docs for version-matched docs. Use for API signatures, guides, and examples.
LangGraph-based agent framework for consistent tool calling with automatic tool loops. Use when you need reliable multi-step task execution with OpenAI-compatible providers (Z.AI/GLM-5, OpenRouter, Groq, DeepSeek, Ollama).
Utiliza esta habilidad cuando el usuario quiera crear, modificar o analizar una nueva "Skill" (habilidad) para Antigravity. Proporciona instrucciones sobre estructura de carpetas, YAML y Markdown.
This skill should be used when the user asks to "develop a concept", "explore a new idea", "brainstorm a system concept", "do concept development", "create a concept document", "run Phase A", "define the problem and architecture", or mentions concept exploration, feasibility studies, concept of operations, system concept, architecture exploration, solution landscape, or NASA Phase A.
Python port of Claude Code agent harness — tools, commands, task orchestration, and CLI entrypoint via oh-my-codex
Comprehensive guide for building production-grade LLM applications using LangChain's chains, agents, memory systems, RAG patterns, and advanced orchestration
Ming Court Code —— Standardize Claude Code development processes using the institutional framework of the Ming Dynasty court. Three-level adaptive modes: Oral Edict (rapid execution), Court Debate (structured solution), Morning Court (multi-agent parallel processing).
Use this skill when you learn one or more design pattern(s) in the Langroid (multi) agent framework, and want to make a note for future reference for yourself. Use this either autonomously, or when asked by the user to record a new pattern.
Connect an AI agent to Handlebar governance platform