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概要と使いどころ
TypeScript-only skill for generating and debugging high-resolution AI images through sub2api OpenAI-compatible APIs. Use this whenever the user wants a TS/Node sub2api image generator, 4K image generation, stream=true /v1/images/generations or /v1/responses image generation, Cloudflare 524 timeout avoidance, partial image capture, or SUB2API_BASE_URL/SUB2API_API_KEY based image generation.
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 you need CRAP score and coverage risk analysis to find high-risk code before refactoring or release. Keywords: CRAP score, risk hotspots, cyclomatic complexity, test coverage gaps, coverage threshold.
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。
JP's signature red-team pass — "how would I break this?" Argue against your own approach before proceeding. Trigger on any high-stakes decision, architecture choice, or before marking work complete.
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 Chinese PPT pages through a prompt-to-image-to-editable-PPT workflow. Use when the user wants 中文PPT图片提示词, PPT image prompts, 16:9中文PPT页面图片, 直接生成PPT图片, 根据提示词生成图片, 把图片/PDF/截图复刻成可编辑PPT, 转成可编辑PPTX, 按图片完全复刻PPT, or full production from topic/source material to generated page images and editable PowerPoint slides with editable text, cards, tables, lines, callouts and high-quality icon/image assets.
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。
Crie designs de websites premium com qualidade Awwwards como componentes React (.jsx) que pareçam ter sido construídos por uma agência de primeira linha cobrando R$250k+ por projeto. Use esta skill sempre que o usuário pedir um website, landing page, portfólio, ou componente web que deve parecer caro, premium, luxo, editorial, high-end, ou de qualidade agência. Também dispare quando o usuário mencionar Awwwards, FWA, design premiado, ou referenciar marcas como Apple, Aesop, Bottega Veneta, Stripe, ou qualquer marca luxury/fashion/design-forward. Dispare quando o usuário disser coisas como "faça parecer profissional", "faça parecer caro", "quero que fique realmente bom", "design de alta qualidade", "não genérico", ou expressar insatisfação com aesthetics típicos de websites gerados por IA. NÃO dispare para dashboards, admin panels, ferramentas internas, ou UI funcional onde aesthetics são secundárias à utilidade — a skill padrão frontend-design cuida disso.
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。
Biblioteca do Facebook para busca eficiente de similaridade e clustering de vetores densos. Suporta bilhões de vetores, aceleração GPU e vários tipos de índice (Flat, IVF, HNSW). Use para busca k-NN rápida, recuperação de vetores em larga escala ou quando você precisa de busca pura de similaridade sem metadados. Melhor para aplicações de alto desempenho.
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。
Serve LLMs com alta throughput usando PagedAttention do vLLM e continuous batching. Use ao fazer deploy de APIs LLM em produção, otimizar latência/throughput de inferência, ou servir modelos com memória GPU limitada. Suporta endpoints compatíveis com OpenAI, quantização (GPTQ/AWQ/FP8) e tensor parallelism.
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。
Otimiza inferência de LLM com NVIDIA TensorRT para máxima vazão e latência mínima. Use para implantação em produção em GPUs NVIDIA (A100/H100), quando você precisa de inferência 10-100x mais rápida que PyTorch, ou para servir modelos com quantização (FP8/INT4), batching em voo e escalabilidade multi-GPU.
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。
Framework PyTorch de alto nível com classe Trainer, treinamento distribuído automático (DDP/FSDP/DeepSpeed), sistema de callbacks e boilerplate mínimo. Escala de laptop para supercomputador com o mesmo código. Use quando quiser loops de treinamento limpos com boas práticas integradas.
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 distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.
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。
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
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。
Load this skill whenever the project contains text, UI components, icons, form controls, data visualisations, or focus indicators — in short, almost every project. Under no circumstances hard-code colour values without verifying contrast ratios. Absolutely always ensure text meets 4.5:1, large text meets 3:1, and non-text UI elements meet 3:1 against adjacent colours. Test in light mode, dark mode, and forced-colors (high contrast) mode.
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。
Load this skill whenever the project supports light/dark mode, colour theme switching, high-contrast mode, or responds to prefers-color-scheme. Under no circumstances hard-code colours that break in alternative themes. Absolutely always test colour contrast in both light and dark themes, and respect user OS-level colour preferences via CSS media queries.
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。
[Process] Use when the developer wants something explained or taught, or wants to know HOW TO REVIEW a change — by default the current working tasks + changes in context, or whatever the prompt names (a plan, a subsystem, a decision, a concept, a bug). AI derives WHAT to explain from the prompt and ALWAYS delivers a teacher-and-coach review guide, high level first then detail: what was done, a VISUAL MAP (system flowchart, domain ERD, sequence diagrams), the user stories and business rules with their REAL test-case IDs, a REVIEW PATH naming which files to open first and in what order with an exit criterion per stage, the technical concepts needed to follow it, how it works, why THIS solution, every alternative option with pros/cons, the trade-offs accepted, the blast radius, HOW TO TEST AND DEMO the change, the developer's decision levers, and written challenge prompts that provoke the reader to pressure-test the work. Works at ANY scope — from one line of code to the whole project: it SIZES the target into a scope tier, DECOMPOSES a large one into understanding groups, BREAKS the work into tasks before the first deep read, and ACCUMULATES the report group by group on disk so a huge explanation stays complete instead of thinning out. Writes the full report to a single combined markdown file (plans/reports/understand-*.md) that opens with a detailed summary section — or delivers it in full in chat when Step 3 finds no git-ignored directory for it — and always summarizes it in chat. Regardless of coding level. Never interrogates, never quizzes, never blocks.
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。
[Decision Support] Use when pressure-testing irreversible, high-stakes decisions with adversarial AI advisors.
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。
[Document Processing] Use when you need to convert markdown files to PDF with syntax highlighting and custom CSS 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。
[Content] Use when you need to create high-converting copy for marketing materials, social media, landing pages, email campaigns, and product descriptions.
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。
[User-Invoked] Use ONLY when the user explicitly types /dual-ai or /dual-ai <workflow-id> — fans out one prompt, or one workflow invocation per tool, to two fresh parallel AI sessions (Claude Code + Codex CLI), both pre-set to xhigh reasoning effort and full-permission mode before the prompt executes. NEVER auto-activate.
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 UI/flows from cognitive load, error prevention, and accessibility perspectives. Apply when reviewing UX, discussing user confusion, high drop-off, or form usability issues.
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, reviewing, or implementing typography in Apple-platform apps — SwiftUI text styles, hierarchy, readable sizes, monospaced data, custom fonts, labels, captions, and accessibility.
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 or implementing search, filtering, sorting, query bars, and result states in Apple-platform apps — keep search, filter, and sort as separate jobs with clear no-result states.
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 building or modifying SwiftUI views, settings windows, menu-bar UIs, or any surface for the KIKA app — or any calm, premium app you want to feel the same way. Encodes the KIKA Design System v2 (June 2026) — a calm, premium, modern dark UI with first-class light mode, inspired by Cursor, Linear, and high-quality dev tools — that you can adopt or adapt for your own app. Apply it to keep color, typography, spacing, and component styling consistent.
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 or implementing feedback, status, progress, alerts, errors, success states, and live activity indicators in Apple-platform apps — inline status, banners, alerts, notifications, and loading states.
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 or implementing the overall macOS app window shell — titlebar, toolbar, sidebar, content, inspector, window sizing, panels, sheets, and menu bar companion windows.
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。