Total 55,662 skills, AI & Machine Learning has 9246 skills
Showing 12 of 9246 skills
Transform session learnings into permanent capabilities (skills, rules, agents). Use when asked to "improve setup", "learn from sessions", "compound learnings", or "what patterns should become skills".
Bootstrap agentic development environment from agent.toml manifest
Use when validating golden dataset quality. Runs schema checks, duplicate detection, and coverage analysis to ensure dataset integrity for AI evaluation.
Create Manim animations for demo videos. Use when visualizing agent workflows, skill pipelines, or architecture diagrams as animated MP4 overlays
Retrieval-Augmented Generation patterns for grounded LLM responses. Use when building RAG pipelines, constructing context from retrieved documents, adding citations, or implementing hybrid search.
Expert prompt optimization for LLMs and AI systems. Use PROACTIVELY when building AI features, improving agent performance, or crafting system prompts. Masters prompt patterns and techniques.
AI-powered search engine with real-time web grounding and citations
Helps coding agents use vit to discover, follow, skim, and ship software capabilities (caps) over ATProto. Activates when the user mentions vit, beacons, caps, shipping, skimming, following, vetting, or social coding.
Recursive Language Model context management for processing documents exceeding context window limits. Enables Claude to match Gemini's 2M token context capability through chunking, sub-LLM delegation, and synthesis.
Orchestrates complete skill lifecycle from creation to optimization. Use for comprehensive skill development, reviewing skills, or managing skill quality.
Cross-platform skill converter. Parse AgentOps skills into a universal bundle format, then convert to target platforms (Codex, Cursor). Triggers: convert, converter, convert skill, export skill, cross-platform.
Systematic implementation using APEX methodology (Analyze-Plan-Execute-eXamine) with parallel agents, self-validation, and optional adversarial review. Use when implementing features, fixing bugs, or making code changes that benefit from structured workflow.