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概要と使いどころ
Configure and use Elasticsearch for full-text search, custom analyzers, aggregations, and index management. Use when a user needs to design search mappings, write complex queries, build aggregation pipelines, tune relevance scoring, or optimize index performance for search workloads.
日本語の概要は準備中です。原文の説明を表示しています。
You are an expert in Cline, the autonomous AI coding agent for VS Code that can read files, write code, run terminal commands, and use the browser — with human-in-the-loop approval at each step. You help developers use Cline for complex multi-file refactoring, feature implementation, debugging, and codebase exploration where the AI plans and executes while the developer reviews and approves.
日本語の概要は準備中です。原文の説明を表示しています。
Node-based graphical interface for Stable Diffusion workflows. Build complex image generation pipelines by connecting nodes visually. Supports custom nodes, ControlNet, LoRA, upscaling, and advanced workflows with full control over the diffusion process.
日本語の概要は準備中です。原文の説明を表示しています。
Define component variants with CVA. Use when creating variant-based components with Tailwind, building design system tokens, or managing complex conditional class names in React.
日本語の概要は準備中です。原文の説明を表示しています。
Coordinate multiple AI agents working together on complex tasks — routing, handoffs, consensus, memory sharing, and quality gates. Use when tasks involve building multi-agent systems, coordinating specialist agents in a pipeline, implementing agent-to-agent communication, designing swarm architectures, setting up agent orchestration frameworks, or building autonomous agent teams with supervision and quality control. Covers hierarchical, mesh, and pipeline topologies.
日本語の概要は準備中です。原文の説明を表示しています。
GraphQL gives clients exactly the data they need - no more, no less. One endpoint, typed schema, introspection. But the flexibility that makes it powerful also makes it dangerous. Without proper controls, clients can craft queries that bring down your server. This skill covers schema design, resolvers, DataLoader for N+1 prevention, federation for microservices, and client integration with Apollo/urql. Key insight: GraphQL is a contract. The schema is the API documentation. Design it carefully. 2025 lesson: GraphQL isn't always the answer. For simple CRUD, REST is simpler. For high-performance public APIs, REST with caching wins. Use GraphQL when you have complex data relationships and diverse client needs. Use when "graphql, graphql schema, graphql resolver, apollo server, apollo client, graphql federation, dataloader, graphql codegen, graphql query, graphql mutation, graphql, api, apollo, schema, resolvers, dataloader, federation, typescript" mentioned.
日本語の概要は準備中です。原文の説明を表示しています。
Firebase gives you a complete backend in minutes - auth, database, storage, functions, hosting. But the ease of setup hides real complexity. Security rules are your last line of defense, and they're often wrong. Firestore queries are limited, and you learn this after you've designed your data model. This skill covers Firebase Authentication, Firestore, Realtime Database, Cloud Functions, Cloud Storage, and Firebase Hosting. Key insight: Firebase is optimized for read-heavy, denormalized data. If you're thinking relationally, you're thinking wrong. 2025 lesson: Firestore pricing can surprise you. Reads are cheap until they're not. A poorly designed listener can cost more than a dedicated database. Plan your data model for your query patterns, not your data relationships. Use when "firebase, firestore, firebase auth, cloud functions, firebase storage, realtime database, firebase hosting, firebase emulator, security rules, firebase admin, firebase, firestore, cloud-functions, serverless, backend, realtime, authentication, google-cloud" mentioned.
日本語の概要は準備中です。原文の説明を表示しています。
Docker makes "works on my machine" a deployment strategy. Package your app with its dependencies, run it anywhere. But Docker's simplicity hides real complexity. A naive Dockerfile can be 10x larger and slower than it needs to be. This skill covers Dockerfile optimization, multi-stage builds, Docker Compose for development, security hardening, and production patterns. Key insight: your Dockerfile is code. Review it, optimize it, version it. 2025 lesson: Containers aren't VMs. The patterns that work for VMs (install everything, big base images) are anti-patterns for containers. Think small, think immutable, think layers. Use when "docker, dockerfile, container, docker compose, docker build, containerize, docker image, multi-stage build, docker network, docker volume, docker, containers, devops, deployment, infrastructure, security, optimization" mentioned.
日本語の概要は準備中です。原文の説明を表示しています。
Expert in CrewAI - the leading role-based multi-agent framework used by 60% of Fortune 500 companies. Covers agent design with roles and goals, task definition, crew orchestration, process types (sequential, hierarchical, parallel), memory systems, and flows for complex workflows. Essential for building collaborative AI agent teams. Use when "crewai, multi-agent team, agent roles, crew of agents, role-based agents, collaborative agents, crewai, multi-agent, agents, orchestration, roles, collaborative-ai" mentioned.
日本語の概要は準備中です。原文の説明を表示しています。
Expert in creating custom slash commands for Claude Code. Slash commands encode repeatable workflows as markdown files, turning complex multi-step processes into simple one-line invocations. Essential for team standardization, onboarding, and reducing cognitive load during development. Use when "custom command, slash command, workflow template, /command, claude command, project commands, team workflows, claude-code, commands, slash-commands, workflow, automation, templates, productivity" mentioned.
日本語の概要は準備中です。原文の説明を表示しています。
Legendary blog writing that makes readers forget they're reading. This skill combines the narrative mastery of Paul Graham's essays, the technical accessibility of Julia Evans, the conversational wit of Wait But Why, and the viral mechanics of James Clear. Great blog posts don't inform—they transform. They take complex ideas and make them feel obvious. They turn strangers into superfans. They get shared not because someone should read them, but because someone needs to read them. This skill adapts to any topic: cybersecurity that reads like a thriller, AI explainers that feel like conversations, marketing insights that make you screenshot every paragraph, and coding tutorials that make you excited to build. Use when "write a blog post, blog post about, write an article, create content about, explain this topic, write about, long-form content, thought leadership, technical blog, how-to article, tutorial post, educational content, industry analysis, opinion piece, newsletter content, make this engaging, write for developers, explain like, writing, blog, content, articles, long-form, storytelling, technical-writing, thought-leadership, educational, tutorials, explainers, engagement" mentioned.
日本語の概要は準備中です。原文の説明を表示しています。
Keeping codebases healthy, performant, and maintainable - refactoring, performance optimization, and technical debt managementUse when "refactor, optimize, performance, technical debt, cleanup, architecture, speed up, bundle size, memory leak, slow query, code smell, complexity, dead code, performance, refactoring, optimization, technical-debt, architecture, cleanup, bundle, memory" mentioned.
日本語の概要は準備中です。原文の説明を表示しています。
Master the AI tools that automate repetitive work and connect your tools. From simple Zapier integrations to complex AI-powered workflows, reclaim hours every week. Use when "automation, workflow, integrate tools, connect apps, zapier, no-code, automate process, rpa, automation, workflow, integration, no-code, zapier, make, rpa" mentioned.
日本語の概要は準備中です。原文の説明を表示しています。
Design and implement agent-based models (ABM) for simulating complex systems with emergent behavior from individual agent interactions. Use when "agent-based, multi-agent, emergent behavior, swarm simulation, social simulation, crowd modeling, population dynamics, individual-based, " mentioned.
日本語の概要は準備中です。原文の説明を表示しています。
Generates a behavioral scenario acceptance matrix for comprehensive test coverage planning. Maps user scenarios to acceptance criteria with stable IDs. Use when planning test coverage for a complex feature, before a release or milestone review, or when someone asks what is tested.
日本語の概要は準備中です。原文の説明を表示しています。
Anime.js Animation Skill workflow skill. Use this skill when the user needs Advanced JavaScript animation library skill for creating complex, high-performance web animations and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
日本語の概要は準備中です。原文の説明を表示しています。
Model domains and bounded contexts for complex systems. Use when a senior developer needs domain-driven design guidance.
日本語の概要は準備中です。原文の説明を表示しています。
Use when building a feature, refactoring, fixing a complex bug, changing architecture, or starting any non-trivial coding task. 12-stage verified dev workflow from research to deploy.
日本語の概要は準備中です。原文の説明を表示しています。
Maintain a structured task list for the current session. Use proactively when a request requires 3+ distinct steps, the user provides multiple items, or complex work benefits from explicit progress tracking. Storage persists via Muninn config across container death. Adapted from Claude Code's TodoWrite tool.
日本語の概要は準備中です。原文の説明を表示しています。
Skill-aware orchestration with context routing. Decomposes complex tasks into skill-typed subtasks, extracts targeted context subsets, executes subagents in parallel, and synthesizes results. Self-answers trivial lookups inline. No SDK dependency — uses raw HTTP via httpx. Use when tasks require multiple analytical perspectives, when context is large and subtasks only need portions, or when orchestrating-chat-agents spawns too many redundant subagents.
日本語の概要は準備中です。原文の説明を表示しています。
Sentence-level and section-level craft for instructions Claude will actually follow, in any container — project instructions, a standalone prompt, or skill body text. Use when the text exists or is being drafted and the question is quality: "why is Claude ignoring this instruction", "rewrite this prompt so it works", "improve my project instructions", "make this instruction stick", "is this too prescriptive", "how much structure does Sonnet need versus Opus". Covers imperative construction, positive framing, strategic-versus-procedural calibration per model, extended thinking, complexity scaling, and a quality checklist. For deciding WHICH container the instruction belongs in, use crafting-instructions. For building, testing and packaging a whole skill directory, use creating-skill.
日本語の概要は準備中です。原文の説明を表示しています。
Systematic research methodology for building comprehensive, current knowledge on any topic. Requires web_search tool. Use when questions require thorough investigation, recent developments post-cutoff, synthesis across multiple sources, or when Claude's knowledge may be outdated or incomplete. Triggered by "Research", "Investigate", "What's current on", "Latest info on", complex queries needing validation, or technical topics with recent changes.
日本語の概要は準備中です。原文の説明を表示しています。
Generate hierarchical _FEATURES.md files that describe what a codebase DOES from a user/consumer perspective, anchored to source symbols via tree-sitting. Supports large complex codebases through feature-driven decomposition into sub-feature files. Uses a multi-pass synthesis: orientation → detail → overview rewrite. Use when someone says "what does this do", "document features", "feature inventory", "_FEATURES.md", or needs to understand a codebase's purpose before modifying it. Complements tree-sitting (structural) with semantic (why/what-for) layer.
日本語の概要は準備中です。原文の説明を表示しています。
Advanced swarm orchestration patterns for research, development, testing, and complex distributed workflows
日本語の概要は準備中です。原文の説明を表示しています。