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概要と使いどころ
Design, implement, review, and audit Android Jetpack Compose UI/UX for phone interfaces. Use when a request concerns concrete Compose layout, components, interaction, accessibility, or visual behavior. Do not activate for framework or dependency presence alone; non-UI Android work is excluded.
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。
Integrate and maintain Robelest Convex Auth in apps by always checking upstream before implementation. Use when adding auth setup, updating auth wiring, migrating between upstream patterns, or troubleshooting @robelest/convex-auth behavior across projects.
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 before creative or constructive work (features, architecture, behavior). Transforms vague ideas into validated designs through disciplined reasoning and collaboration.
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。
Mandatory skills, conventions, and behavioral rules for Avalonia UI development using the Zafiro toolkit.
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 market conditions, geographic opportunities, pricing, consumer behavior, and product validation across Google Maps, Facebook, Instagram, Booking.com, and TripAdvisor.
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。
Understand audience demographics, preferences, behavior patterns, and engagement quality across Facebook, Instagram, YouTube, and TikTok.
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。
Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.
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You are an API mocking expert specializing in realistic mock services for development, testing, and demos. Design mocks that simulate real API behavior and enable parallel development.
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。
Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring—where even top agents achieve less than 50% on real-world benchmarks
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Use by any agent before writing specs, editing code, or changing workflow files when the change could add compatibility behavior, aliases, silent fallbacks, or default-value fallbacks.
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。
Reference OpenCode docs when implementing skills, plugins, MCPs, or config-driven behavior.
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 traceable functional test conditions across positive, negative, boundary, and error behavior with observable expectations.
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 traceable accessibility checks that combine scanners with observable keyboard, focus, semantic, and assistive-technology behavior.
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 or refactor an existing SKILL.md and its bundled resources — a smaller always-loaded core, conditional references, preserved behavior, lean/guided consumer profiles, and an A/B protocol to compare a candidate with the previous version. Use when a skill repeats itself, loads references on every run, triggers too broadly or misses legitimate requests, or needs its efficiency measured across models. Do NOT use for writing a new skill from scratch, refactoring application code, translating a skill verbatim, or performing the target skill's own task.
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 before any creative work - creating a feature, building a component, adding functionality, or changing behavior - to explore intent and design before 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。
Analyze a completed phase diff for high-confidence behavior-preserving simplifications and apply only explicitly approved proposals. Use after execution and before review to reduce duplication, dead code, needless complexity, or avoidable inefficiency.
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 an existing skill must be refactored to cut context and ambiguity without losing behavior, safety or fallbacks — 'refatorar a skill', 'reduzir esta SKILL.md', 'revisar skill com métricas' — with before/after metrics, preserved invariants and three review rounds.
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 encountering any bug, test failure, or unexpected behavior, before proposing any fix
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 code structure, readability, and maintainability without changing external behavior through systematic refactoring techniques like extracting functions, removing duplication, simplifying conditionals, and applying design patterns. Use when reducing technical debt, extracting functions or classes, removing code duplication, simplifying complex conditionals, renaming for clarity, applying design patterns, improving code organization, reducing coupling, increasing cohesion, or maintaining test coverage during structural 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。
Implement test-driven development (TDD) workflow using the red-green-refactor cycle. Use when writing new features, fixing bugs, or refactoring existing code. Always write the failing test first, then implement minimal code to pass, then refactor. Essential for ensuring code reliability, preventing regressions, improving design through testability requirements, documenting expected behavior through tests, enabling confident refactoring, and maintaining high code quality standards throughout the development process.
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。
Write comprehensive end-to-end tests that verify complete user workflows, integration between components, and system behavior from user perspective using Playwright, Cypress, or similar frameworks. Use when testing user flows, verifying feature integration, testing across real browsers, ensuring UI interactions work correctly, validating form submissions end-to-end, testing authentication flows, catching regressions, automating QA processes, testing API integrations, or building confidence in production deployments.
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。
Apply systematic root cause analysis and debugging methodologies to diagnose and fix bugs, test failures, and unexpected behavior. Use when encountering production issues, investigating test failures, diagnosing performance problems, tracing error sources through call stacks, analyzing logs and stack traces, reproducing inconsistent bugs, debugging race conditions, investigating memory leaks, or applying scientific method to problem-solving before proposing fixes.
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。
Trace bugs backward through call stacks and execution flows to identify the original source of errors, invalid data, or incorrect behavior. Use when debugging complex issues, tracing error origins, investigating data corruption, following execution paths, identifying where invalid data enters the system, or finding root causes of cascading failures.
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 asked to debug, fix a bug, investigate an error, or do root cause analysis, and when users report errors, stack traces, unexpected behavior, or say something stopped working.
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。