Total 30,738 skills, AI & Machine Learning has 4962 skills
Showing 12 of 4962 skills
Research how to implement a phase standalone, investigating implementation approaches before planning, or re-researching after planning is complete. Triggers include "research phase", "investigate phase", "how to implement", "research implementation", and "phase research".
Resume work from a previous session, restoring context after a break, continuing work after /clear, or picking up where you left off. Triggers include "resume work", "continue work", "pick up where I left off", "restore context", and "resume session".
Surface Claude's assumptions about a phase approach before planning, checking what Claude thinks, or validating understanding before planning. Triggers include "list assumptions", "what are you thinking", "show assumptions", "phase assumptions", and "what's the plan".
Execute all plans in a phase with wave-based parallelization, running phase execution, or completing phase work. Triggers include "execute phase", "run phase", "execute plans", "run the phase", and "phase execution".
Comprehensive knowledge of Claude Agent SDK architecture, tools, hooks, skills, and production patterns. Auto-activates for agent building, SDK integration, tool design, and MCP server tasks.
This skill should be used when the user asks to "build background agent", "create hosted coding agent", "set up sandboxed execution", "implement multiplayer agent", or mentions background agents, sandboxed VMs, agent infrastructure, Modal sandboxes, self-spawning agents, or remote coding environments.
Provides guidance for creating effective Claude Code skills with proper YAML frontmatter, directory structure, and best practices. Activates when the user mentions "create skill", "new skill", "スキル作成", "SKILL.md", "skill development".
Intelligent Prompt Generator v2.0 - Supports three modes: Portrait/Cross-Domain/Design, with semantic understanding, common sense reasoning, and consistency checking
Write and optimize prompts for AI-generated outcomes across text and image models. Use when crafting prompts for LLMs (Claude, GPT, Gemini), image generators (Midjourney, DALL-E, Stable Diffusion, Imagen, Flux), or video generators (Veo, Runway). Covers prompt structure, style keywords, negative prompts, chain-of-thought, few-shot examples, iterative refinement, and domain-specific patterns for marketing, code, and creative writing.
Advanced RAG with Self-RAG, Corrective-RAG, and knowledge graphs. Use when building agentic RAG pipelines, adaptive retrieval, or query rewriting.
Retrieval-Augmented Generation (RAG) system design patterns, chunking strategies, embedding models, retrieval techniques, and context assembly. Use when designing RAG pipelines, improving retrieval quality, or building knowledge-grounded LLM applications.
Analyze emotion — mood classification, energy, valence, genre detection