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概要と使いどころ
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
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 new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, update or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
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。
Interpret YouTube Analytics, TikTok Analytics, and video performance data. Identifies trends, explains metrics, and provides actionable recommendations for growth. Use when analyzing video performance, understanding metrics, or optimizing channel 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。
Ad Performance Auditor — analyze existing ad campaigns and identify optimization opportunities
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。
Legacy v1 (voiceover-led, GSAP + HyperFrames). Use when making, directing or rescuing a product launch video, promo, teaser, demo reel, sizzle, feature-announcement film or animated product explainer built from code — and when an existing one looks basic, reads as a slideshow, has reveals that miss the voiceover, an invisible cursor, an inaudible sound effect, a clipped or too-quiet mix, or every video coming out looking the same. Covers SaaS, apps, hardware, e-commerce, dev tools, services. Keywords include motion design, storyboard, voiceover sync, kinetic typography, GSAP, HyperFrames, Remotion, film grain, LUFS, ffmpeg.
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。
Identifies bug-introducing commits using SZZ-style analysis based on bug-fixing commits, commit history, and code blame information. Use this skill when you need to trace bugs back to their origin, identify which commits introduced bugs, analyze bug-fix commits to find root causes, perform software repository mining for bug analysis, or conduct empirical studies on software defects. Triggers when users ask to find bug-introducing commits, identify when a bug was introduced, trace bug origins, perform SZZ analysis, or analyze bug-fixing commits.
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 code statically to detect potential functional bugs including null dereferences, incorrect condition checks, unreachable code, inconsistent state updates, logic errors, resource leaks, and type mismatches. Report suspicious code locations with detailed explanations, severity levels, and confidence assessments. Use when reviewing code for bugs, performing code audits, or when the user asks to find bugs, detect issues, analyze code for problems, or perform static analysis.
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。
Automatically updates a codebase to a new language version, framework version, or library update while ensuring all tests still pass. Use this skill when migrating Python 2→3, upgrading framework versions (React, Django, Angular), updating dependencies, or performing any version migration where tests define correct behavior. The skill analyzes failing tests caused by migration, categorizes errors (import errors, API changes, type errors, behavior changes), proposes systematic fixes, and verifies that test-observable behavior remains unchanged. Triggers when users ask to migrate code versions, upgrade dependencies while keeping tests passing, update framework versions, or perform test-guided version migrations.
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 comprehensive code reviews identifying bugs, security issues, performance problems, code quality concerns, and best practice violations. Use when reviewing pull requests, examining code changes, evaluating new code, assessing code quality, or providing feedback on implementations. Analyzes code for correctness, security vulnerabilities, performance bottlenecks, maintainability issues, test coverage, documentation quality, and adherence to coding standards. Produces structured markdown reviews with categorized findings, severity ratings, specific examples, and actionable recommendations. Triggers when users ask to review code, check pull requests, evaluate implementations, find bugs, or assess code quality.
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。
Analyzes and optimizes code for better performance, memory usage, and efficiency. Use when code is slow, memory-intensive, or inefficient. Supports Python and Java optimization including execution speed improvements, memory reduction, database query optimization, and I/O efficiency. Provides before/after examples with detailed explanations of why optimizations work, complexity analysis, and measurable 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。
Performs abstract interpretation over source code to infer possible program states, variable ranges, and data properties without executing the program. Reports potential runtime errors including out-of-bounds accesses, null dereferences, type inconsistencies, division by zero, and integer overflows. Use when analyzing code for potential runtime errors, performing static analysis, checking safety properties, or verifying program behavior without execution.
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 supplier performance scorecards with KPIs, quality metrics, delivery performance, cost management, and improvement plans
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 institutional-grade comparable company analyses with operating metrics, valuation multiples, and statistical benchmarking in Excel/spreadsheet format. **Perfect for:** - Public company valuation (M&A, investment analysis) - Benchmarking performance vs. industry peers - Pricing IPOs or funding rounds - Identifying valuation outliers (over/under-valued) - Supporting investment committee presentations - Creating sector overview reports **Not ideal for:** - Private companies without comparable public peers - Highly diversified conglomerates - Distressed/bankrupt companies - Pre-revenue startups - Companies with unique business models
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。
Monthly social media performance review for SMBs. Analyses post-level and account-level data from Instagram, LinkedIn, Facebook, or TikTok. Identifies what worked, what didn't, and why. Produces a client-ready report and specific recommendations that feed back into the content calendar. Accepts CSV exports, screenshots, or manual data input.
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。
Audit component performance and identify optimization opportunities with actionable 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。
Perform actions and handle dynamic, async UI so tests adapt to 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。
Perform comprehensive audit of interface quality across accessibility, performance, theming, and responsive design. Generates detailed report of issues with severity ratings and recommendations.
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 new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
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。
The HyperFrames composition contract — build one renderable project. Use for composition structure, the `data-*` timing attributes, `class="clip"`, tracks, sub-compositions, variables, framework-owned media playback, deterministic-render rules, and validation. Also covers Tailwind projects and the STORYBOARD.md / SCRIPT.md plan formats. Read before writing composition HTML.
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。
Production-grade TypeScript reference for React & Next.js frontend development. Covers type narrowing, component Props, generic hooks, discriminated unions, as const, satisfies, Zod validation, TanStack Query, server/client boundaries, forms, state management, performance, accessibility, debugging, and code review. Use when the user works with TypeScript in React or Next.js: type errors, Props design, generics, API typing, SSR/CSR boundaries, hydration issues, form validation, state management, performance, or code review. Also use for "how should I type this?", "why does this type error happen?", or any architectural decision involving TypeScript in a frontend context.
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。
Author a HyperFrames slideshow — a presentation, pitch deck, or interactive deck with discrete slides, fragment reveals, branching, hotspot navigation, and built-in presenter mode with speaker notes; also converts an existing page into a deck. Output is a navigable deck, not a rendered MP4. If the user didn't explicitly ask for a slideshow, confirm before authoring. Unclear → /hyperframes.
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 the HyperFrames CLI development loop: init, add, catalog, capture, lint, check, snapshot, compare, grade-compare, preview, play, present, beats, keyframes, single or batch render, publish, cloud, cloudrun, feedback, lambda, doctor, browser, info, upgrade, skills, compositions, docs, benchmark, telemetry, transcribe, auth, tts, and remove-background. Also use when diagnosing build or render failures. validate, inspect, and layout are deprecated aliases; use check. Covers local, HeyGen-hosted cloud, AWS Lambda, and Google Cloud Run rendering.
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 web application performance through code splitting, lazy loading, caching strategies, and Core Web Vitals monitoring. Use when improving page load times, implementing service workers, or reducing bundle sizes.
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。
| Nuxt 5 production optimization: hydration, performance, testing with Vitest, deployment to Cloudflare/Vercel/Netlify, and migration from Nuxt 4. Use when: debugging hydration mismatches, optimizing performance and Core Web Vitals, writing tests with Vitest, deploying to Cloudflare Pages/Workers/Vercel/Netlify, or migrating from Nuxt 4 to Nuxt 5.
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。