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概要と使いどころ
Use when polling external AIs (OpenAI, Anthropic) outside the host session for a neutral second opinion on a roadmap, diff, prompt, or file set — or 'cross-check with another model'.
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 mapping competitors, naming defensibility, and finding white-space — moat reasoning, where-to-play, where-not-to-play. Triggers on 'who are we competing with', 'what's our moat'.
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。
Grounded brand decisions from a curated corpus — archetype, voice, naming, colour psychology, logo-style fit, messaging frameworks, archetype→type mapping. Use to ground brand strategy and identity.
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。
Guia completo para criar diagramas de software usando sintaxe Mermaid. Use quando usuários precisarem criar, visualizar ou documentar software por meio de diagramas, incluindo diagramas de classe (modelagem de domínio, design orientado a objetos), diagramas de sequência (fluxos de aplicação, interações de API, execução de código), fluxogramas (processos, algoritmos, jornadas do usuário), diagramas de relacionamento de entidades (esquemas de banco de dados), diagramas de arquitetura C4 (contexto do sistema, containers, componentes), diagramas de estado, git graphs, gráficos de pizza, gráficos de Gantt ou qualquer outro tipo de diagrama. Acionadores incluem solicitações para "diagram", "visualize", "model", "map out", "show the flow" ou ao explicar arquitetura de sistema, design de banco de dados, estrutura de código ou fluxos de usuário/aplicação.
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。
Skill de pesquisa profunda alimentado por NotebookLM MCP. Conduz pesquisa estruturada em múltiplas fontes (análise de mercado, inteligência competitiva, análise de tendências, pesquisa de prospects) usando Google NotebookLM como mecanismo de pesquisa, depois entrega briefs formatados e artefatos opcionais de estúdio (slides, podcasts de áudio, vídeos, infográficos, relatórios, mapas mentais).
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 and edit editable Excalidraw diagrams in Canvas Notebook through the Scene-Service tools. Use for diagrams, flows, sketches, architecture maps, visual explanations, or requested .excalidraw documents.
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 when configuring axe-core scans, reviewing automated accessibility test results, or writing tests that use @axe-core/playwright, @axe-core/react, or similar integrations. Provides a quick reference to axe 4.x rule IDs, their WCAG mapping, and default severity levels.
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。
[Project Management] Use when creating user stories, writing acceptance criteria, analyzing requirements, or mapping business processes.
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。
[Project Management] Use when you need to map and visualize feature dependencies between modules, services, and work items.
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 generating a single dense technical architecture, reference poster, or system diagram image for a software project. Produces a source-grounded bitmap diagram with topology, primitives, ingest/process flow, core logic, state scopes, tiers/modules, surfaces, runtime cards, and strict semantic color rules.
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。
Critically analyze whether a product, repo, skill, plugin, harness, or architecture vision still fits the real application, user intent, implementation, evidence, and likely future direction. Use when asked to assess vision vs application, predict future fit, critique roadmap direction, analyze strategic intent, or decide whether to keep, refine, pivot, or kill a plan.
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 asks to create, add, convert, publish, or deploy a blog post from a draft, notes, Markdown, outline, or topic. Turns a draft into a complete, SEO/GEO-optimized post wired into the site (template, blog index, sitemap, routing) with QA and deploy. Framework-agnostic — discover the project's own conventions first.
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 a macOS app needs a TCC permission or touches private data — the map of which API, Info.plist key, and entitlement each permission needs, pre-prompt explanation patterns, denied-state recovery with System Settings deep links, and honest privacy copy.
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 adding, reviewing, or debugging Launch at Login in a macOS app — SMAppService registration, the requiresApproval state, a Settings toggle that reflects reality, and migration off deprecated login-item APIs.
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。
Plan a huge chunk of work — more than one agent session can hold — as a shared map of decision tickets on your issue tracker, and resolve them one at a time until the way to the destination is clear.
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。
Produce comprehensive synthesis with explicit citations from multiple ordinary public-web sources via the Tavily CLI. Use for detailed reports, comparisons, market or literature research, and questions whose answer requires multi-source web evidence rather than a quick lookup. Do not use for simple discovery (tavily-search), one known URL (tavily-extract), one-site URL discovery or bulk extraction (tavily-map/crawl), or research centered on named social, community, career, code, media, authenticated, or cross-platform sources (Agent Reach). Takes 30-120 seconds.
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。
Discover ordinary public webpages with LLM-optimized Tavily search results. Use when no specific URL is known and the user needs a quick public-web lookup, articles, recent news, sources, or domain-filtered results. This is the default Tavily leaf for simple public-web discovery. Do not use when the user already supplied the target URL (use tavily-extract), wants URLs under one known site (tavily-map), wants many pages' content (tavily-crawl), needs a full cited synthesis (tavily-research), or needs named platforms, login state, platform-native content, or cross-platform collection (Agent Reach).
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。
Extract clean markdown, text, or targeted chunks from one or more known, publicly accessible webpage URLs via the Tavily CLI. Use when the URLs are already supplied or discovered and the user wants page content rather than more URLs. Do not use to find an unknown page (tavily-search), list a site's URL structure (tavily-map), bulk-extract a site section (tavily-crawl), or retrieve named platform, authenticated, cookie-dependent, or platform-native content (Agent Reach). Can process up to 20 public URLs per request.
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 publishing, updating, moving, or removing DeepSeek Harness documentation website pages; editing website/docs.ts mappings or navigation; diagnosing a page missing from the VitePress site; fixing projected documentation links; or running the docs:dev, docs:check, and doc-sync workflow after website-content changes.
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。
All animation knowledge for HyperFrames — atomic motion rules, multi-phase scene blueprints, scene transitions, broader motion-design techniques, AND the seven runtime adapters (GSAP default, plus Lottie, Three.js, Anime.js, CSS keyframes, Web Animations API, TypeGPU). Use for any motion or animation task: pick 2-4 rules and compose, or load a blueprint, or look up runtime-specific API (e.g. GSAP eases / Lottie player / Three.js mixer). Also covers auditing an existing composition's choreography (animation map) and 24 named text-animation effects. HyperFrames-native: single paused timeline, seek-safe, deterministic.
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。
Map application security findings to OWASP Top 10 categories and generate remediation checklists. Use for normalized AppSec review outputs and category-level prioritization.
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。
Actively enumerate in-scope hosts and services, then produce normalized network mapping artifacts.
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。
Aggregate findings and generate multi-format pentest reports with remediation roadmap and risk scoring.
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。