Total 56,830 skills, AI & Machine Learning has 9448 skills
Showing 12 of 9448 skills
AI image generation using Google Gemini (Gemini) and OpenAI GPT-Image. Generate, edit, iterate, and create assets.
Multi-agent orchestration for complex tasks. Use when tasks require parallel work, multiple agents, or sophisticated coordination. Triggers include requests for features, reviews, refactoring, testing, documentation, or any work that benefits from decomposition into parallel subtasks. This skill defines how to orchestrate work using cc-mirror tasks for persistent dependency tracking and TodoWrite for real-time session visibility.
Methodology for effective AI-assisted software development. Use when helping users build software with AI coding assistants, debugging AI-generated code, planning features for AI implementation, managing version control in AI workflows, or when users mention "vibe coding," Cursor, Windsurf, or similar AI coding tools. Provides strategies for planning, testing, debugging, and iterating on code written with LLM assistance.
Process multimodal inputs (images, video, audio, PDFs) with Gemini 3 Pro. Covers image understanding, video analysis, audio processing, document extraction, media resolution control, OCR, and token optimization. Use when analyzing images, processing video, transcribing audio, extracting PDF content, or working with multimodal data.
Redis semantic caching for LLM applications. Use when implementing vector similarity caching, optimizing LLM costs through cached responses, or building multi-level cache hierarchies.
AI-powered X/Twitter research via xAI Grok. Returns AI SUMMARIES with analysis, not raw tweets. Use for "what's trending", "social sentiment", "summarize X discussion about", "analyze X conversation about", "research topic on X". For RAW tweet data, use x-user-timeline, x-tweet-search, x-tweet-fetch instead. Requires XAI_API_KEY.
Scaffold development rules for AI coding agents. Auto-invoked when user asks about setting up rules, coding conventions, or configuring their AI agent environment.
Designs multi-step agent workflows with tool usage, retry logic, state management, and budget controls. Provides orchestration diagrams, tool execution order, fallback strategies, and cost limits. Use for "AI agents", "agentic workflows", "multi-step AI", or "autonomous systems".
Meta-skill for creating new Claude Code skills with configurable execution modes. Supports sequential (fixed order) and autonomous (stateless) phase patterns. Use for skill scaffolding, skill creation, or building new workflows. Triggers on "create skill", "new skill", "skill generator".
DeFi fundamentals and cross-chain analytics using DefiLlama-style data. Use when you want to find undervalued protocols, screen by TVL/revenue growth vs token price, compare sectors, or run data-driven crypto research beyond pure memes.
Turn an idea into a functional, demo-ready prototype using AI-assisted “vibe coding” (timeboxed build loop, prompt pack, build plan, demo script, and safety checks). Use for rapid prototyping and proving concepts in AI & Technology.
Create an AI Evals Pack (eval PRD, test set, rubric, judge plan, results + iteration loop). Use for LLM evaluation, benchmarks, rubrics, error analysis/open coding, and ship/no-ship quality gates for AI features.