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概要と使いどころ
Comprehensive autonomous design quality audit across accessibility (WCAG 2.2), performance, theming, responsive/adaptive design, and anti-pattern detection. Produces a prioritized report with severity ratings and fix recommendations. Use when: 'audit design', 'check accessibility', 'a11y audit', 'design review', 'UI quality check', 'WCAG audit', 'design quality'.
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Token architecture, component specifications, and slide generation. Three-layer tokens (primitive→semantic→component), CSS variables, spacing/typography scales, component specs, strategic slide creation. Use for design tokens, systematic design, brand-compliant presentations.
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 design token usage across a product for consistency and coverage.
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。
An inspired interpretation of Shopifi's design language — a cinematic commerce platform that runs two parallel design tracks. The marketing-hero and product-narrative pages live on near-black canvases with full-bleed photography of merchants, giant Neue Haas Grotesk display type at thin weights, and a single black-pill CTA stroked in white. The transactional pages (pricing, signup, dashboards) flip to a cream-mint canvas with pastel aloe and pistachio greens, the same pill button vocabulary, and Inter for UI body. The two tracks share typographic DNA but diverge sharply in canvas polarity — and that choice is the brand.
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问题 + 成功指标 + 范围 + user stories + 设计 + 发布 + 待解决
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。
Kaggle-first end-to-end competition workflow for scored submissions. Use when Codex must run Kaggle or competitive ML workflows through scored submission, including code competitions, validation, metrics, policy-safe public notebook/discussion intel, tabular/text/image modeling, tuning, ensembling/stacking, proactive multi-notebook architectures, producer notebooks that train models and export private Kaggle artifact datasets, downstream consumer notebooks, Kaggle GPU offload, kagglehub access, hidden-test debugging, and public score retrieval.
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 SurrealDB 3 architect and developer skill (tracks v3.1.4+). SurrealQL mastery, multi-model data modeling (document, graph, vector, time-series, geospatial), schema design, security, deployment, performance tuning, SDK integration (JS, Python, Go, Rust, Java, .NET, C, PHP, Swift, Kotlin, Ruby), Surrealism WASM extensions, SurrealML scope coverage (preview), built-in MCP (v3.1+) and standalone SurrealMCP, LangChain Python integration, editor tooling (LSP v0.1.6, tree-sitter, CodeMirror v1.0.6, VS Code/JetBrains/Neovim/Zed), and ecosystem integrations (Surrealist v3.9, Surreal-Sync, SurrealFS, SurrealKit v0.7, n8n, Agent Skills, setup-surreal). Universal skill for 30+ AI agents.
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。
Draft and explain persistent goal-loop prompts for long-running agent work with clear stop conditions.
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。
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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。
Connects Claude Code, Codex, Cursor, and other MCP hosts to Writingmate for model discovery, text comparison, image generation, and video generation with Seedance, Sora, Veo, Kling, PixVerse, and other available 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。
AI code reviewer grounded in classic software engineering books for catching design smells, coupling issues, and architectural risks.
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 production-ready AI agents with PydanticAI — type-safe tool use, structured outputs, dependency injection, and multi-model support.
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。
Docker containerization expert with deep knowledge of multi-stage builds, image optimization, container security, Docker Compose orchestration, and production deployment patterns. Use PROACTIVELY for Dockerfile optimization, container issues, image size problems, security hardening, networking, and orchestration challenges.
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。
An enterprise-marketing canvas faithful to Carbon Design System: white surfaces, charcoal type, IBM Blue (#0f62fe) as the single confident accent, and a deliberately flat-square aesthetic where corners stay at 0–4px. Type runs IBM Plex Sans at light weight 300 for display sizes (a brand signature) and 400/600 for body and emphasis. Cards live as thin-bordered tiles with no shadow; sections separate via subtle gray rows. The chrome is square, the typography is light, and the only color in the system is one assertive blue — the result reads as old-world enterprise gravitas reframed for the cloud era.
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。
在 CLI 环境下做 Android APK 逆向时使用。适用于 APK 解包、Java 反编译、smali 修改、重打包、Frida 动态 Hook，以及按需切换到 so/native 分析。优先使用本机已安装的 jadx、apktool、frida、adb、ida-reverse、radare2。
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。
Verify fix commits address audit findings without new bugs
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。
Drift is the divergence between declared infrastructure and live infrastructure.
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。
.NET / C# 二进制逆向。当目标是 .NET assembly（PE 头含 CLR、.exe/.dll 托管程序）、C# 编译产物（含 NativeAOT）、红队 Sharp* 工具（Rubeus / SharpHound / SharpHound 等）、.NET 混淆程序（ConfuserEx / SmartAssembly / Babel / Eazfuscator）、.NET loader / info-stealer / 套壳 malware 时使用。优先用 dnSpyEx + de4dot，需要 AI 直接操作时联动 dnSpy MCP。不用于纯 native 二进制（走 reverse-engineering / ida-reverse）。
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。
Security audit of a codebase — web apps, APIs, services, CLI tools, libraries, daemons, and more. Use when asked to find security bugs, do a security review, audit for vulnerabilities, or pen-test the code. Focuses on exploitable issues with real impact, not theoretical concerns or industry-standard 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。
Build production-ready LLM applications, RAG systems, and intelligent agents. Use when implementing AI features, chatbots, vector search, or agent orchestration.
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Expert in CrewAI - the leading role-based multi-agent framework used by 60% of Fortune 500 companies. Covers agent design with roles and goals, task definition, crew orchestration, process types (sequential, hierarchical, parallel), memory systems, and flows for complex workflows. Essential for building collaborative AI agent teams. Use when: crewai, multi-agent team, agent roles, crew of agents, role-based agents.
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。
Automates Azure OpenAI model deployment by checking capacity across regions and deploying to the best available option.
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Provides reverse engineering techniques. Use when the main job is to understand how a compiled, obfuscated, packed, or virtualized target works before exploiting or solving it, including binaries, APKs, WASM, firmware, custom VMs, bytecode, malware-like loaders, and anti-debug or anti-analysis logic. Do not use it when the vulnerability is already understood and the remaining task is exploitation; use pwn instead. Do not use it for pure web workflows, log or disk forensics, or standalone crypto problems unless reversing the implementation is the real blocker.
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。
SurrealDB Surrealism WASM extension development. Write Rust functions, compile to WASM, deploy as database modules. Part of the surreal-skills collection.
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。