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概要と使いどころ
Create standout, technically ambitious interfaces that feel extraordinary through cinematic transitions, advanced motion, heavy rendering, or other high-ambition implementation work. Use when the user wants to wow, impress, go all-out, or push a feature beyond conventional UI polish—not when simple visual confidence or routine cleanup is enough.
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。
Add moments of joy, personality, and surprise through success states, empty states, loading moments, hover details, and celebratory polish once the fundamentals already work. Use when the user wants delight, charm, personality, or memorable micro-interactions—not when the main need is baseline cleanup or stronger visual impact.
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。
Set up Claude Code git safety guardrails that block dangerous git commands before execution. Use when the user asks to prevent git push, hard reset, git clean, destructive checkout/restore, or branch deletion from Claude Code hooks.
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。
Manage track lifecycle: archive, restore, delete, rename, and cleanup
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 software architect specializing in modern architecture patterns, clean architecture, microservices, event-driven systems, and DDD. Reviews system designs and code changes for architectural integrity, scalability, and maintainability. Use PROACTIVELY for architectural decisions.
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。
Base implementation skill for this repository across .NET/C#, backend APIs, database/ORM, frontend Vue/Quasar, and Rust with Clean Architecture rules. Use when the user asks to build features, fix bugs, refactor modules, or improve code-level performance, and use specialized skills as inheritance layers when available.
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。
Implement and refactor frontend features using Vue and Quasar with repository architecture, theming, UX, and performance standards. Use when tasks involve components, composables, Pinia, routing, i18n/UI behavior, responsive layouts, or frontend clean architecture 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。
Extend dev-software-engineer with .NET/C# backend specialization for Clean Architecture, CQRS, EF Core, and production-ready API practices. Use when tasks involve ASP.NET endpoints, handlers, services, dependency injection, MediatR, migrations, or backend performance/resilience.
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。
Extend dev-software-engineer with .NET/C# backend specialization for Clean Architecture, CQRS, EF Core, and production-ready API practices. Use when tasks involve ASP.NET endpoints, handlers, services, dependency injection, MediatR, migrations, or backend performance/resilience and should follow the base implementation workflow.
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。
Remove a GSD workspace and clean up worktrees
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 a clean PR branch by filtering out .planning/ commits — ready for code review
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。
Archive accumulated phase directories from completed milestones
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。
Scrape webpage content, extract metadata, download images, and prepare for import/migration to AEM Edge Delivery Services. Returns analysis JSON with paths, metadata, cleaned HTML, and local images.
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。
Bulk-retouch a folder of portrait photos using Adobe tools — designed for wedding photographers and event photographers who need fast, walk-away batch processing. Use this skill when the user says "retouch my photos", "batch process these portraits", "process my wedding photos", "clean up this folder of images", "run my headshots through Adobe", or uploads/selects a folder of photos and wants them polished and ready to review. Automatically applies auto-straighten, auto-tone, and auto-light to every image. Outputs a preview grid and download folder. Access: 🔐 Signed-In required | Gen AI: ❌
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, revise, or evaluate repository Agent Skills when the user asks to write a SKILL.md, improve triggers or information hierarchy, restructure references/scripts/assets, or diagnose skill predictability; do not use for product code, AGENTS.md initialization, general prompt editing, or automatic repository-wide cleanup.
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。
Analyze source data, tables, CSV/XLSX extracts, metrics, or experiment results with explicit data-authenticity checks. Use for profiling, cleaning assumptions, statistical summaries, segmentation, trend analysis, or "analyze this data"; do not use for spreadsheet file surgery, chart design only, database migrations, or claims without data provenance.
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。
Simplify a bounded code area when the user explicitly requests behavior-preserving refactoring or a named complexity/readability problem is the accepted task; do not trigger automatically after implementation, during every review, for adjacent cleanup, or when behavior may change.
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。
Clean editorial-style interfaces. Warm monochrome palette, typographic contrast, flat bento grids, muted pastels. No gradients, no heavy shadows.
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。
Creates ephemeral preview deployments for each pull request with automatic deployment, unique URLs, and cleanup on PR close. Use for "preview deployments", "PR environments", "ephemeral environments", or "review apps".
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。
Converts documents into clean, chunked datasets suitable for embeddings and vector search. Produces chunked JSONL files with metadata, deduplication logic, and quality checks. Use when preparing "training data", "vector datasets", "document processing", or "embedding data".
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。
Elite website image-to-code skill for Codex. For visually important web tasks, it must first generate the design image(s) itself, deeply analyze them, then implement the website to match them as closely as possible. In Codex, it must prefer large, readable, section-specific images instead of tiny compressed boards, generate fresh standalone images for sections or detail views instead of cropping old ones, avoid lazy under-generation, avoid cards-inside-cards-inside-cards UI, and keep the hero clean, spacious, readable, and visible on a small laptop.
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。
Overrides default LLM truncation behavior. Enforces complete code generation, bans placeholder patterns, and handles token-limit splits cleanly. Apply to any task requiring exhaustive, unabridged output.
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 and implements data retention policies with archival strategies, compliance requirements, automated cleanup jobs, and cold storage migration. Use for "data retention", "data archival", "GDPR compliance", or "storage optimization".
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 clean React/Vue component skeletons with TypeScript types, prop variants, styling hooks, test files, Storybook stories, and usage documentation. Use when users request "create a component", "scaffold component", "new React component", or "generate component boilerplate".
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。