1.1万 件 ・ 関連度順
概要と使いどころ
Use when a release review needs machine-derived evidence from git history — hotspot risk and change-coupling analyzers. Triggers on 'hotspot', 'what changes together', 'release forensics'.
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 working with database architecture, MariaDB/MySQL tuning, indexing strategies, slow queries, or multi-connection patterns — even when the user just says 'this query is slow'.
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 creating an API endpoint or HTTP route handler — detects the project stack and routes to the matching carve-out (laravel-api-endpoint, nextjs-patterns, symfony-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。
Use when a diff may break system boundaries, dependency direction, or cross-service contracts — fifth judge dispatched by /review-changes alongside the four standard judges.
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 capturing an architectural decision — file naming, next ADR number, Status / Context / Decision / Consequences, index regen; fires even without saying 'ADR'.
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。
Address GitHub PR review comments at line, file, and PR level by fetching, evaluating, fixing, committing, and resolving feedback. Use when invoked as `$pr-resolve-review-feedback` or when the user asks to resolve PR feedback.
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 facing 2+ independent tasks that can be worked on without shared state or sequential dependencies
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 for any question about a codebase, its architecture, file relationships, or project content — especially when graphify-out/ exists, where the question should be treated as a graphify query first. Turns any input (code, docs, papers, images, videos) into a persistent knowledge graph with god nodes, community detection, and query/path/explain tools.
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 you have a spec or requirements for a multi-step task, before touching 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。
Review a written plan or design doc through a designer's lens before implementation - seven passes over information architecture, interaction states, emotional arc, AI-slop risk, design-system alignment, responsive and accessibility coverage, and unresolved decisions. Each dimension is rated 0-10 with an explicit statement of what would make it a 10, then the plan is edited to get there. Use when a plan has a UI surface and you want the design gaps closed before code is written. Not for auditing a live site.
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。
Build and sharpen a project's domain model. Use when the user wants to pin down domain terminology or a ubiquitous language, record an architectural decision, or when another skill needs to maintain the domain model.
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。
Evaluate design from a UX perspective, assessing visual hierarchy, information architecture, emotional resonance, cognitive load, and overall quality with quantitative scoring, persona-based testing, automated anti-pattern detection, and actionable feedback. Use when the user asks to review, critique, evaluate, or give feedback on a design or component.
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。
Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.
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。
Move issues and external PRs through a state machine of triage roles — categorise, verify, grill if needed, and write agent-ready briefs.
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。
Implements any user intent, requirement, story, bug fix or change request by producing clean working code artifacts that follow the project's existing architecture, patterns and conventions. Use when the user wants to build, fix, tweak, refactor, add or modify any code, component or feature.
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。
Validate PRD, UX, Architecture and Epics specs are complete. Use when the user says "check implementation readiness".
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。
Walk every branching path and boundary condition in content, report only unhandled edge cases. Orthogonal to adversarial review - method-driven not attitude-driven. Use when you need exhaustive edge-case analysis of code, specs, or diffs.
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。
Conduct technical research on technologies and architecture. Use when the user says they would like to do or produce a technical research report
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 the user asks how code works, wants to understand architecture, trace execution flows, or explore unfamiliar parts of the codebase. Examples: "How does X work?", "What calls this function?", "Show me the auth flow"
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。
React composition patterns that scale. Use when refactoring components with boolean prop proliferation, building flexible component libraries, or designing reusable APIs. Triggers on tasks involving compound components, render props, context providers, or component architecture. Includes React 19 API 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。
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
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。
[Architecture] Use when scaffolding reusable OOP/SOLID project foundations before feature implementation.
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。
[Documentation] Use when scanning the codebase to (re)generate ONE project-reference doc. Parameterized by `--target=<key>`: project-structure | backend-patterns | frontend-patterns | scss-styling | design-system | code-review-rules | domain-entities | feature-spec | docs-index | e2e-tests | integration-tests | seed-test-data | ui-system. Shared 4-phase scan engine; per-target detail lives in references/targets.md. `ui-system` is an orchestrator meta-target (`kind: orchestrator`) that runs the 3 UI child scans in parallel instead of the 4-phase engine.
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。
[Debugging] Use when analyzing or optimizing performance bottlenecks: database queries, N+1 fan-out, indexing, API latency, memory/GC, concurrency and pool saturation, algorithmic complexity (O(n²)), network/protocol round trips, frontend rendering and Core Web Vitals, caching, and distributed/resilience paths. Calibration constants and domain laws (latency ladder, Little's Law, utilization knee, CWV thresholds, symptom→cause triage) live in references/performance-knowledge.md.
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。