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Found 6,548 Skills
Expert guidance on AI Agent Harness architecture based on the comprehensive Claude Code analysis book
Expert guide for Nous Research's Hermes Agent framework with self-improving learning loops, three-layer memory, and automatic Skill creation
Sync, search, and classify X/Twitter bookmarks locally with full-text search, LLM classification, and agent integration
agent-team: List tasks with optional run, agent, or status filters.
Build autonomous self-evolving AI agents with vision-grounded memory that operate computers through a perceive-reason-act cycle
Expert knowledge of agentic AI design patterns for autonomous agent development
Research collection of reconstructed prompt patterns and architectures for agentic AI coding assistants
Implementation guide for 17+ agentic AI architectures using LangChain and LangGraph for building sophisticated AI agents
A curated collection of research papers and resources on agentic reasoning for Large Language Models, organized by planning, tool use, search, self-evolution, and multi-agent systems.
Guides engineering of multi-agent systems—agent roles and specialization, orchestration topologies (supervisor, peer-to-peer, hierarchical, blackboard), task decomposition and routing, inter-agent messaging (A2A-style patterns), shared vs partitioned state, fan-out/fan-in and DAG workflows, synchronization and consensus, conflict resolution, fault tolerance and retries across agents, cost/latency/token budgets, cross-agent observability, testing multi-agent flows, and deployment (queues, durable workflows). Framework-agnostic; high-level LangGraph, Deep Agents, and agenthub—not single-agent loops (agentic-ai-developer), ML training (ai-engineer), strategy-only whiteboard (enterprise-strategist), or PM planning (technical-program-manager). Use for multi-agent system, multi-agent engineer, agent orchestration, supervisor agent, agent topology, fan-out fan-in, agent handoff protocol, multi-agent workflow, agent coordination, blackboard pattern, hierarchical agents, A2A, agent DAG, multi-agent architecture.
Select and configure evaluation metrics for an AI agent. Guides through metric selection using use-case recommendations, custom LLM-based metric creation with prompt engineering, and agent default attachment. Use when user says "set up metrics", "configure metrics", "create a metric", "what metrics should I use", "add evaluation criteria", or "customize scoring".
Reference and consulting skill for OpenClaw — a messaging gateway that connects AI agents to multiple communication platforms (Telegram, Discord, Slack, WhatsApp, iMessage, and more). Use when working with OpenClaw configuration, channels, Gateway setup, skills, cron jobs, MCP servers, memory, OAuth, or troubleshooting. Also use when the user asks how to implement a use case on their OpenClaw bot (daily morning brief, research workflows, competitive radar, decision playbook), how to add a new channel, or how to connect the CodeAlive context engine. Triggers on requests like "configure openclaw", "add Discord to my bot", "set up morning brief", "gateway not starting", "connect CodeAlive search", "OAuth re-auth", or any close paraphrase. Companion of install-openclaw-to-yc — install both together.