3,731 件 ・ 関連度順
概要と使いどころ
The original v1 taste-skill, preserved for projects depending on its exact behavior. The current default is `design-taste-frontend` (v2 experimental), which is a substantial rewrite. Use this v1 install name only if you need exact backward compatibility.
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, 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。
Improve unclear UX copy, error messages, microcopy, labels, and instructions to make interfaces easier to understand. Use when the user mentions confusing text, unclear labels, bad error messages, hard-to-follow instructions, or wanting better UX writing.
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 wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI tasks.
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 strategic color to features that are too monochromatic or lack visual interest, making interfaces more engaging and expressive. Use when the user mentions the design looking gray, dull, lacking warmth, needing more color, or wanting a more vibrant or expressive palette.
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 knowledge base. Provides documentation types, audiences, best practices, and antipatterns for technical documentation creation.
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。
Saga Pattern knowledge base. Provides patterns, antipatterns, and PHP-specific guidelines for saga orchestration, choreography, and distributed transaction audits.
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。
Outbox Pattern knowledge base. Provides patterns, antipatterns, and PHP-specific guidelines for transactional outbox, polling publisher, and reliable messaging audits.
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。
SOLID principles knowledge base for PHP 8.5 projects. Provides quick reference for SRP, OCP, LSP, ISP, DIP with detection patterns, PHP examples, and antipattern identification. Use for architecture audits and code quality 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。
Stability Patterns knowledge base. Provides patterns, antipatterns, and PHP-specific guidelines for Circuit Breaker, Retry, Rate Limiter, Bulkhead, and resilience audits.
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。
Layered Architecture knowledge base. Provides patterns, antipatterns, and PHP-specific guidelines for traditional N-tier/Layered Architecture audits.
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。
Event Sourcing knowledge base. Provides patterns, antipatterns, and PHP-specific guidelines for Event Sourcing architecture audits.
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。
DDD architecture knowledge base. Provides patterns, antipatterns, and PHP-specific guidelines for Domain-Driven Design audits.
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。
Hexagonal Architecture (Ports & Adapters) knowledge base. Provides patterns, antipatterns, and PHP-specific guidelines for Hexagonal Architecture audits.
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。
Detects test antipatterns and code smells in PHP test suites. Identifies 15 smells (Logic in Test, Mock Overuse, Fragile Tests, Mystery Guest, etc.) with fix recommendations and refactoring patterns for testability.
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。
PSR-1 and PSR-12 coding standards knowledge base for PHP 8.5 projects. Provides quick reference for basic coding standard and extended coding style with detection patterns, examples, and antipattern identification. Use for code style audits and compliance 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 DDD Factory for PHP 8.5. Creates factories for complex domain object instantiation with validation and encapsulated creation logic. Includes unit tests.
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。
Action-Domain-Responder pattern knowledge base. Provides patterns, antipatterns, and PHP-specific guidelines for ADR (web-specific MVC alternative) audits.
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。
CQRS architecture knowledge base. Provides patterns, antipatterns, and PHP-specific guidelines for Command Query Responsibility Segregation audits.
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 Architecture knowledge base. Provides patterns, antipatterns, and PHP-specific guidelines for Clean Architecture and Hexagonal Architecture audits.
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 guidance for reviewing academic manuscripts submitted to journals, particularly in political science, economics, and quantitative social sciences. Use when asked to review, critique, or provide feedback on academic papers, research designs, or empirical strategies. Emphasizes methodological rigor, causal identification strategies, and constructive feedback on research design.
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。
Academic paper search across 14+ scholarly platforms including arXiv, PubMed, Google Scholar, Web of Science, Semantic Scholar, Sci-Hub, and more. Use for literature review, research discovery, and citation management.
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 knowledge graph for autonomous coding. Use when storing relationships, querying connected knowledge, building project understanding, or maintaining semantic memory.
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 3D computer vision labeling tools, workflows, and AI-assisted annotation for LiDAR, point clouds, and sensor fusion. Covers SAM4D/Point-SAM, human-in-the-loop architectures, and vertical-specific training strategies. Activate on '3D labeling', 'point cloud annotation', 'LiDAR labeling', 'SAM 3D', 'SAM4D', 'sensor fusion annotation', '3D bounding box', 'semantic segmentation point cloud'. NOT for 2D image labeling (use clip-aware-embeddings), general ML training (use ml-engineer), video annotation without 3D (use computer-vision-pipeline), or VLM prompt engineering (use prompt-engineer).
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。