Total 50,634 skills, AI & Machine Learning has 8486 skills
Showing 12 of 8486 skills
Build Next.js web applications with Google Gemini Nano Banana image generation APIs (gemini-2.5-flash-image, gemini-3-pro-image-preview). Use when creating image generators, editors, galleries, or any app integrating conversational image generation with server actions, API routes, and storage. Use for "image generation app", "nano banana", "text to image", "AI image generator", or "gemini image". Do NOT use for non-Gemini models, Python/Go backends, model fine-tuning, or image classification/input tasks.
Evaluate and improve skills through measured testing. Run trigger evaluations to test whether skill descriptions cause correct activation, optimize descriptions via automated train/test loops, benchmark skill output quality with A/B comparisons, and validate skill structure. Use when user says "improve skill", "test skill triggers", "optimize description", "benchmark skill", "eval skill", or "skill quality". Do NOT use for creating new skills (use skill-creator-engineer).
Constructive critique through 5 HackerNews commenter personas with evidence-based claim validation. Use when user wants devil's advocacy, stress testing, or critical review of ideas, docs, architecture, or code. Use for "roast", "critique this", "poke holes", "devil's advocate", "stress test", or "what's wrong with". Do NOT use for code review (use systematic-code-review), implementation changes, or performance profiling without a specific critique request.
Agent skill for arch-system-design - invoke with $agent-arch-system-design
Use when cognee is a Python AI memory engine that transforms documents into knowledge graphs with vector and graph storage for semantic search and reasoning. Use this skill when writing code that calls cognee's Python API (add, cognify, search, memify, config, datasets, prune, session) or integrating cognee-mcp. Covers the full public API, SearchType modes, DataPoint custom models, pipeline tasks, and configuration for LLM/embedding/vector/graph providers. Do NOT use for general knowledge graph theory or unrelated Python libraries.
PUA Loop — Autonomous iterative development with PUA pressure. Runs continuously until the task is completed, no user interaction required. Combines the Ralph Loop iteration mechanism with PUA quality enforcement. Triggered by: '/pua:pua-loop', 'Auto Loop', 'loop mode', 'Keep Running', 'Auto Iteration'
Give Claude Code full internet access with three-layer channel dispatch, CDP browser automation, and parallel sub-agent task splitting
Vector embeddings with HNSW indexing, sql.js persistence, and hyperbolic support. 75x faster with agentic-flow integration. Use when: semantic search, pattern matching, similarity queries, knowledge retrieval. Skip when: exact text matching, simple lookups, no semantic understanding needed.
Generate, edit, upscale, variate, and style-transfer images using the AgentOS multi-provider image pipeline with automatic fallback and character consistency.
Orchestrate web-search, deep-research, content-extraction, hacker-news, stealth-browser, and news-search for comprehensive information gathering.
Use when the user asks to "improve my agent", "self-improving agent", "auto-tune my agent", "iterate on my agent prompt", "fix my agent based on test results", "close the loop on agent quality", "auto-improve agent prompt", "use eval results to improve agent", "optimize my prompt based on failures", "rewrite my prompt", or describes agent self-improvement, prompt iteration from run results, or automated agent quality loops. Covers the full diagnose → propose → apply → re-validate loop for VAPI agents (squads + tool definitions) and for self-hosted agents (custom websocket servers, including the offline / pasted-prompt degenerate variant).
Karpathy's LLM Wiki: build/query interlinked markdown KB.