Total 31,401 skills, AI & Machine Learning has 5086 skills
Showing 12 of 5086 skills
Trace knowledge artifact lineage and sources. Find orphans, stale citations. Triggers: "where did this come from", "trace this learning", "knowledge lineage".
Comprehensive AI writing detection patterns and methodology. Provides vocabulary lists, structural patterns, model-specific fingerprints, and false positive prevention guidance. Use when analyzing text for AI authorship or understanding detection patterns.
A skill that analyzes 18-month scenarios using news headlines as input. The main analysis is performed by the scenario-analyst agent, and a second opinion is obtained from the strategy-reviewer agent. Generates a comprehensive report in Japanese including primary, secondary, tertiary impacts, recommended stocks, and reviews. Example usage: /scenario-analyzer "Fed raises rates by 50bp" Triggers: news analysis, scenario analysis, 18-month outlook, medium-to-long-term investment strategy
Master context engineering for AI agent systems. Use when designing agent architectures, debugging context failures, optimizing token usage, implementing memory systems, building multi-agent coordination, evaluating agent performance, or developing LLM-powered pipelines. Covers context fundamentals, degradation patterns, optimization techniques (compaction, masking, caching), compression strategies, memory architectures, multi-agent patterns, LLM-as-Judge evaluation, tool design, and project development.
Skill for creating AI agent projects using the VoltAgent framework. Guide for CLI setup and manual bootstrapping.
Look up VoltAgent documentation embedded in node_modules/@voltagent/core/docs for version-matched docs. Use for API signatures, guides, and examples.
VoltAgent architectural patterns and conventions. Covers agents vs workflows, project layout, memory, servers, and observability.
Build LiveKit Agent backends in TypeScript or JavaScript. Use this skill when creating voice AI agents, voice assistants, or any realtime AI application using LiveKit's Node.js Agents SDK (@livekit/agents-js). Covers AgentSession, Agent class, function tools with zod, STT/LLM/TTS models, turn detection, and realtime models.
Build autonomous game-playing agents using AI and reinforcement learning. Covers game environments, agent decision-making, strategy development, and performance optimization. Use when creating game-playing bots, testing game AI, strategic decision-making systems, or game theory applications.
Guides creation of high-quality Agent Skills with domain expertise, anti-pattern detection, and progressive disclosure best practices. Activate on keywords: create skill, review skill, skill quality, skill best practices, skill anti-patterns, improve skill, skill audit. NOT for general coding advice, slash commands, MCP development, or non-skill Claude Code features.
Expert in designing, orchestrating, and managing multi-agent systems (MAS). Specializes in agent collaboration patterns, hierarchical structures, and swarm intelligence. Use when building agent teams, designing agent communication, or orchestrating autonomous workflows.
Create, deploy, and interact with agents on TerminalUse. Use when user mentions "tu", "terminaluse", "deploy agent", "create agent", "agent task", "filesystem", or wants to build/test/run an agent.