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Found 1,650 Skills
AI Agent long-term memory system with cross-session, cross-project persistence. Triggers: - /remember - Store memories - /recall - Search memories - /forget - Delete/archive memories - /memory-status - Check status - When needing to persist important conversation insights - When sharing user preferences across projects
Query decomposition for multi-concept retrieval. Use when handling complex queries spanning multiple topics, implementing multi-hop retrieval, or improving coverage for compound questions.
Audit and refactor existing SKILLs. Use when improving drafts, fixing quality, or aligning to spec. For creating new skills from scratch use skill-creator (anthropics/skills).
Use when "CrewAI", "multi-agent systems", "agent orchestration", "AI crews", or asking about "autonomous agents", "agent collaboration", "role-based agents", "agent workflows", "AI team coordination"
Prompt engineering standards and context engineering principles for AI agents based on Anthropic best practices. Covers clarity, structure, progressive discovery, and optimization for signal-to-noise ratio.
Agentica server + Claude proxy setup - architecture, startup sequence, debugging
Searches and retrieves MLflow documentation from the official docs site. Use when the user asks about MLflow features, APIs, integrations (LangGraph, LangChain, OpenAI, etc.), tracing, tracking, or requests to look up MLflow documentation. Triggers on "how do I use MLflow with X", "find MLflow docs for Y", "MLflow API for Z".
Patterns and architectures for autonomous Claude Code loops — from simple sequential pipelines to RFC-driven multi-agent DAG systems.
Comprehensive macOS app development with Swift 6.2, SwiftUI, SwiftData, Swift Concurrency, Foundation Models, Swift Testing, ScreenCaptureKit, and app distribution. Use when building native Mac apps, implementing windows/scenes/navigation/menus/toolbars, persisting data with SwiftData (@Model, @Query,
Fully local multi-agent swarm intelligence simulation engine using Neo4j + Ollama for public opinion, market sentiment, and social dynamics prediction.
Use when users provide vague, underspecified, or unclear requests where they need help defining WHAT they actually want - across ANY domain (writing, analysis, code, documentation, proposals, reports, presentations, creative work). Trigger aggressively when users express VAGUE GOALS ("make this better", "improve our X", "figure out what to include", "I don't know where to start", "kinda lost on what to do", "not sure what this means"), UNDEFINED SUCCESS ("should look professional", "explain this clearly", "make it convincing", "whatever works best", missing constraints/audience/format), COMMUNICATION UNCLEAR ("how do I explain/communicate this", "my team gets confused when I describe it", "help me figure out what to ask about X"), AMBIGUOUS REQUIREMENTS ("analyze the data" without saying what to look for, "improve documentation" without saying how, "make it more robust" without defining robustness, any request with multiple valid interpretations), or META-PROMPTING ("optimize this prompt", "improve my prompt", "make this clearer", "review my instructions", learning about prompt frameworks like CO-STAR/RISEN/RODES, understanding what makes prompts effective). Trigger for non-technical users and ANY situation where the request needs refinement, structure, or clarification before execution can begin. When in doubt about whether a request is clear enough - trigger.
Agent skill for sona-learning-optimizer - invoke with $agent-sona-learning-optimizer