「men」の検索結果

Build animations in React Native and Expo, making the decisions in the order that determines whether they feel right — should it animate, which thread it runs on, which properties, spring or timing, how the gesture hands off, how it degrades. Writes the implementation with Reanimated, Gesture Handler, Expo Router and expo-haptics. Use when animating anything in an Expo app, adding gestures, sheets, screen transitions, press feedback or haptics, or fixing motion that stutters on device. For web animation use `animate`.

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。

Installs and configures Prettier, ESLint, EditorConfig, and other code quality tools to enforce consistent code style across the team. Generates config files, npm scripts, editor settings recommendations, and CI integration suggestions. Use when users request "setup prettier", "add eslint", "configure code formatting", or "enforce code style".

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。

Unifies API response patterns across endpoints including pagination format, error structure, status codes, response envelopes, and versioning strategy. Provides contract documentation, shared TypeScript types, middleware utilities, and migration plan. Use when standardizing "API contracts", "response formats", "API conventions", or "API consistency".

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 an animation from scratch, making the decisions in the order that determines whether it feels right — should it animate at all, what purpose, which tool, which properties, which curve and duration, how it interrupts, how it exits. Writes the implementation. Use when asked to animate something, add motion, make a component feel alive, or build a transition. For critiquing existing motion use review-animations; for auditing a whole codebase use improve-animations.

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 mock API servers for testing and development with MSW, json-server, or custom handlers. Use when users request "API mocking", "mock server", "MSW setup", "test fixtures", or "mock API responses".

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。

Designs background job processing systems with queue integration (BullMQ/Celery), job definitions, retry policies, exponential backoff, idempotent execution, and monitoring hooks. Use when implementing "background jobs", "task queues", "async processing", or "job workers".

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。

Brand voice, visual identity, messaging frameworks, asset management, brand consistency. Activate for branded content, tone of voice, marketing assets, brand compliance, style guides.

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 comprehensive disaster recovery procedures with automated backup scripts, restore procedures, validation checks, and role assignments. Use for "database backup", "disaster recovery", "data restore", or "DR 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。

Generates Bruno collection files (.bru) from Express, Next.js, Fastify, or other API routes. Creates organized collections with environments, authentication, and folder structure for the open-source Bruno API client. Use when users request "generate bruno collection", "bruno api testing", "create bru files", or "bruno import".

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。

Defines caching strategies with cache keys, TTL values, invalidation triggers, consistency patterns, and correctness checklist. Provides code examples for Redis, CDN, and application-level caching. Use when implementing "caching", "performance optimization", "cache strategy", or "Redis caching".

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 CRUD REST API endpoints with request validation, TypeScript types, consistent response formats, error handling, and documentation. Includes route handlers, validation schemas (Zod/Joi), typed responses, and usage examples. Use when building "REST API", "CRUD endpoints", "API routes", or "backend endpoints".

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。

Optimizes CI/CD pipeline speed by implementing effective caching for dependencies, Docker layers, build outputs, and test results. Provides before/after performance metrics and best practices. Use for "CI caching", "pipeline optimization", "build speed", or "cache strategy".

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。

Apple's approach to interface design and fluid, physical motion, translated for the web. Use when building or reviewing gesture-driven UI, spring animations, drag/swipe/sheet interactions, momentum and interruptible transitions, translucent materials and depth, typography (optical sizing, tracking, leading), reduced-motion, or the design foundations (feedback, spatial consistency, restraint) behind Apple-style interfaces.

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 Spark change needs its authoritative owner, affected boundaries, risks, acceptance criteria, and smallest verifiable slice established before implementation or 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。

Use when a Spark implementation needs an evidence-based review for correctness, ownership, compatibility, failure handling, maintainability, and unnecessary complexity.

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 designing a Spark feature or writing or materially revising a design proposal that needs repository-first research, user input on unresolved key choices, and an owner-aligned implementation plan before code 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。

Use when a working Spark implementation should be simplified without changing its observed behavior, ownership, compatibility, or public contract.

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 complete research workflow — its instructions, skills, data boundaries, and tool connections — must be assessed for portability across AI agents or environments, so each component is explicitly mapped before migration rather than assumed to transfer.

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 authorship order, CRediT contribution roles, or AI-assistance attribution must be recorded transparently for a manuscript, when an author dispute needs an evidence trail, or before a contributorship statement is required at submission; this skill maintains the human-attribution ledger of who contributed what and in which role (authorship order, CRediT taxonomy, revision responsibilities), which is distinct from the disclosure-metadata audit owned by ai-disclosure-auditor.

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 high-stakes analysis, citation set, or decision should be checked by a second independent AI agent that verifies rather than decides, or when disagreement between agents must be surfaced for the human to adjudicate.

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 paired tr.md and en.md files need a parity verdict, when titles, frontmatter, headings, or DOI sets may have drifted between languages, or when a bilingual document is approaching release and its translation coverage needs an audit.

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 designing a course, assessment, or student-feedback workflow and deciding where AI assistance is acceptable, when grading or feedback must stay within academic-integrity and FERPA/KVKK boundaries, or when AI-use rules for students need stating.

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 construct, scale, or key term crosses Turkish and English and conceptual equivalence must be audited: translation and back-translation, construct drift, and culturally bound meaning, before measurement or cross-cultural claims.

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 AI contribution metadata must match the actual workflow, when model alias and dated identifiers need auditing, when verified and fabricated citation counts feed a release decision, or when a venue's AI disclosure statement needs evidence behind it.

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。