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概要と使いどころ
Activate ATLAS pattern recognition mode. Identify repeated patterns, extract essential characteristics, and create reusable abstractions from concrete examples.
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。
Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.
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 only when the user explicitly invokes obra test-driven-development for iron-law examples. Core TDD is docs/ai/skills/tdd/SKILL.md. Do not use this for docs-only, formatting-only, or generated-mirror 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。
Manages shadcn components and projects — adding, searching, fixing, debugging, styling, and composing UI, including chat interfaces. Provides project context, component docs, and usage examples. Applies when working with shadcn/ui, component registries, presets, --preset codes, or any project with a components.json file. Also triggers for "shadcn init", "create an app with --preset", or "switch to --preset".
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。
Explicit polish reference for concentric radius, optical alignment, surface depth, contextual icons, and hit areas. Use only after Core frontend rules and packages/ui. Do not restyle product apps from these examples.
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。
Explicit layout reference for grouping, alignment, reading order, and progressive disclosure. Use only after Core frontend rules. Do not restyle product apps from these examples.
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。
MATLAB/GNU Octave numerical computing: matrices, linear algebra, ODEs, signal processing, optimization, statistics, scientific visualization. MATLAB-syntax examples run on both. For Python use numpy/scipy; for statistical modeling use statsmodels.
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。
Provides structured AWS cost optimization guidance using five pillars (right-sizing, elasticity, pricing models, storage optimization, monitoring) and twelve actionable best practices with executable AWS CLI examples. Use when optimizing AWS costs, reviewing AWS spending, finding unused AWS resources, implementing FinOps practices, reducing EC2/EBS/S3 bills, configuring AWS Budgets, or performing AWS Well-Architected cost reviews.
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 comprehensive TypeScript documentation using JSDoc, TypeDoc, and multi-layered documentation patterns for different audiences. Use when creating API documentation, architectural decision records (ADRs), code examples, and framework-specific patterns for NestJS, Express, React, Angular, and Vue.
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。
Provides patterns and code examples for building Next.js 16+ applications with App Router architecture. Use when creating projects with App Router, implementing Server Components and Client Components ("use client"), creating Server Actions for forms, building Route Handlers (route.ts), configuring caching with "use cache" directive (cacheLife, cacheTag), setting up parallel routes (`@slot`) or intercepting routes, migrating to proxy.ts, or working with App Router file conventions (layout.tsx, page.tsx, loading.tsx, error.tsx).
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。
Provides patterns to generate comprehensive REST API documentation using SpringDoc OpenAPI 3.0 and Swagger UI in Spring Boot 3.x applications. Use when setting up API documentation, configuring Swagger UI, adding OpenAPI annotations, implementing security documentation, or enhancing REST endpoints with examples and schemas.
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。
Provides Amazon S3 patterns and examples using AWS SDK for Java 2.x. Use when working with S3 buckets, uploading/downloading objects, multipart uploads, presigned URLs, S3 Transfer Manager, object operations, or S3-specific configurations.
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 extracting first-party expertise from a subject-matter expert before writing content. Produces a knowledge document of contrarian takes, specific examples, and surprising outcomes that AI can't fabricate.
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 tools, scripts, and CLIs that an agent will call, so the interface teaches its own use instead of a wall of prose and examples. Use when building an MCP server or tool definition, writing an agent-facing script, or when an agent keeps misusing a tool it already has.
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 querying or calling pay-per-token foundation models, or when creating, updating, listing, or querying Unity Gateway (also called Unity AI Gateway) services, including model provider services, MCP services, system.ai services, and three-part Unity Catalog service names (catalog.schema.service). Also use for managing spend budgets and usage alerts on Unity Gateway, and for migrating from legacy AI Gateway. Also use when a workload with Model Serving endpoint permissions (for example CAN_QUERY) gets PERMISSION_DENIED querying a three-part model name, since serving-endpoint access does not grant access to a Unity Gateway service. Not for configuring legacy AI Gateway on Model Serving endpoints; use databricks-model-serving for that.
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。
Plans, drafts, and refines technical tutorials for developers. Use when writing step-by-step guides or getting-started walkthroughs backed by working code.
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。
Searches GitHub for existing implementations, libraries, or patterns. Use when finding code examples or prior art on a topic during a research session.
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。
Writes and restructures technical documentation - READMEs, tutorials, how-to guides, user guides, architecture docs, onboarding guides, runbooks and SOPs, troubleshooting guides, release notes, and knowledge base articles - grounded in the actual code or product, with commands and examples verified where possible. Use when the user asks to document a project, feature, system, or process, write or fix a README, explain a codebase to new developers, turn notes into a guide, or make existing docs clearer. For endpoint-by-endpoint API reference or OpenAPI specs, use api-documentation-writer; for CLAUDE.md or AGENTS.md files, use claude-md-writer.
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。
Recommend font combinations for different use cases. Provide Google Fonts alternatives to premium fonts with hierarchy examples.
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 comprehensive API documentation including endpoint descriptions, request/response examples, authentication guides, error codes, and SDKs. Creates OpenAPI/Swagger specs, REST API docs, and developer-friendly reference materials. Use when users need to document APIs, create technical references, or write developer documentation.
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。
Route Flower repository tasks for app authoring, strategies and mods, local simulation and deployment, Flower Datasets and examples, and repository maintenance.
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。
Operate the Fengshenbang-LM Fengshen package for pipelines, model families, data/training utilities, examples, and conversion planning.
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 DPM-Solver and DPM-Solver++ single-file samplers for diffusion ODE sampling, PyTorch/JAX integration, ScoreSDE/DDPM examples, and Stable Diffusion acceleration.
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。
Route and use the repository's PyTorch reinforcement-learning examples across tabular control, DQN, on-policy actor-critic, and off-policy continuous control.
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。