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A three-surface marketing system organized around alternating black, white, and PlayStation Blue chapters that scroll past the viewer like a console launch trailer. Each section has a single editorial purpose — hero photography, console product render, PS Plus tier callout, news strip — and each owns one of three full-bleed canvas modes. The chrome is unusually quiet for a gaming brand: bright PlayStation Blue (`#0070d1`) carries every primary CTA as a fully-rounded pill, the proprietary SST face renders display copy at a signature weight 300 (light) for an airy, premium feel, and a crisp 8px-radius secondary card system carries product info on either canvas mode. The system never decorates — no gradient backgrounds on chrome, no atmospheric mesh, no drop shadows beyond a faint section-divide. Imagery does all the heavy lifting: console glamour shots, game key art, and PS Plus tier illustrations occupy 60-90% of every section, with copy compressed into a small editorial slot.

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。

A luxury-automotive brand whose marketing surfaces read as cinematic editorial. The base canvas is **near-black** (`#181818`) holding pure white display type; white-canvas bands appear only inside specific editorial contexts (preowned listings, pricing tables). The single brand voltage is **Rosso Corsa** (`#da291c`) — the iconic Ferrari racing red — used scarcely on primary CTAs, the Cavallino mark, and Formula 1 race-position highlights. Type runs **FerrariSans** at modest weights (display 500, body 400) — never bombastic. Spacing follows an explicit 8px token ladder (`xxxs` 4px through `super` 128px); generous editorial pacing throughout. The brand's strongest visual signature is the **full-bleed cinematic hero photograph** that fills the viewport top with car photography, model details, or trackside livery — followed by a tighter editorial body layout below.

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 a risk matrix or heatmap that quantifies what could break by business impact × probability, runs failure mode analysis on the top items, and maps test coverage to risk zones. Includes stakeholder interview frameworks and continuous reassessment. Run this BEFORE test-strategy or test-planning. Use when: "risk assessment," "risk matrix," "risk heatmap," "what could break," "critical paths," "failure modes," "where to focus testing." Not for: multi-quarter QA direction — use test-strategy. Not for: a single sprint/release test plan — use test-planning. Not for: hands-on session-based bug hunting — use exploratory-testing. Related: test-strategy, test-planning, release-readiness, qa-metrics.

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。

Choose and run ACU-only, adaptive PPU in-kernel timeline, or optional bounded joint analysis for a PPU kernel. Use for device-level bottleneck diagnosis, kernel-internal critical-path questions, or evidence that genuinely needs both; do not require all three modes.

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。

Systematically QA test any application — web apps, native macOS apps, Electron apps, CLI tools, interactive REPLs, or anything on screen. Three modes: browser (chromux/CDP, fast, DOM-level), computer (MCP computer-use, screenshot + pixel clicks, any app), and cli (tmux, send-keys + capture-pane for interactive terminals). Auto-selects mode or accepts --browser / --computer / --cli override. Use when asked to "qa", "QA", "test this site", "test this app", "find bugs", "test and fix", "fix what's broken", "dogfood", "exploratory test", "bug hunt", "QA this app", "사이트 테스트", "앱 테스트", "브라우저 QA", "화면 보고 테스트해줘", "네이티브 앱 테스트", "screen test". Three tiers: Quick (critical/high only), Standard (+ medium), Exhaustive (+ cosmetic). Produces before/after health scores, fix evidence, and a ship-readiness summary.

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。

Turn a rough idea, a bug, or a batch of unsolved problems into well-structured GitHub issue(s) and file them with `gh`, auto-classifying type + labels from the content (recommend, then confirm) and following Rove's conventions (beginner-friendly framing, concrete file pointers, an acceptance checklist, zero AI/Anthropic attribution). Handles single, batch, and "file the unsolved problems" modes. Use when the user says "file an issue", "open a GitHub issue", "draft a good first issue", "batch these as issues", "上报 issue", "提个 issue", "报个 bug", "把没解决的发上去", or wants to hand low-priority tasks to outside contributors. Distinct from the daemon-owned internal issue store (`rove api issue-*`); this skill is for outward-facing GitHub 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。

Turn one line ("a turbofan jet engine", "a mechanical watch", "an LVAD heart pump") into a photoreal, physics based, interactive 3D simulation of that machine in a single HTML file, plus a 20 to 30 second film to post it. Real proportions in metres, real materials (PBR metals, paints, polymers, glass), studio lighting with soft shadows, moving parts driven by a small solver that computes real numbers (thrust, torque, rpm, flow, pressure, efficiency), and modes to explode it, cut it open with clean section caps, x-ray it, slow it down, label it and break it. Use this whenever someone asks to build, simulate, visualise, explain or "show how X works" for any machine, engine, mechanism, device, instrument or piece of hardware, wants an interactive 3D model or a cutaway, or wants a video of a machine for a post, even if they never say "simulation" or "three.js".

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。

AgentCall (agentcall.dev) — Join a video meeting (Google Meet, Teams, Zoom) as an AI bot with voice and visual presence. Supports audio-only mode with voice intelligence (barge-in, interruptions), text-to-speech mode, and webpage modes for custom UI. Use when asked to join a call, attend a meeting, or participate in a video conference.

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。

Generate, audit, or update GitHub READMEs with project-type-aware structure, voice calibration, and SEO/AEO discoverability guidance. Three modes: generate (new), audit (check existing), update (patch). Detects repo type and adapts sections, tone, and badges accordingly.

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。

Builds and revises a complete skill DIRECTORY — SKILL.md, scripts, references, assets — and packages it. Use for "create a skill for X", "turn this into a skill", "update/improve this skill", "why doesn't my skill trigger", "review this SKILL.md", "package this skill", or when a repeated procedure should become a reusable artifact. Enforces the structure that makes skills work — a concrete procedure rather than a goal statement, an explicit applicability boundary, failure modes with their signals, a runtime verification step, and a description checked against the existing catalogue for confusability. For choosing whether the instruction should be a skill at all rather than project instructions or a prompt, use crafting-instructions. For writing quality inside the prose, use writing-instructions.

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-assisted pair programming with multiple modes (driver/navigator/switch), real-time verification, quality monitoring, and comprehensive testing. Supports TDD, debugging, refactoring, and learning sessions. Features automatic role switching, continuous code review, security scanning, and performance optimization with truth-score verification.

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 a theming architecture that supports brand variants, dark mode, and high-contrast modes with token mapping.

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。

Generates a fully structured SEO content brief for a target keyword and optionally pushes it to a Notion database. Use this skill whenever the user says 'create a content brief', 'brief this keyword', 'run a content brief for', 'generate a brief', 'write a brief for [keyword]', 'content brief on [topic]', or any variation where someone needs a keyword researched and turned into a structured writing assignment with H1, H2 outline, FAQ, internal links, word count target, and writer notes. Also triggers when the user provides a keyword and asks for an SEO brief, editorial brief, or writing spec. Outputs a mandatory structured format that the text parser maps directly to Notion properties. Supports single-keyword and batch (CSV) modes.

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 image generation and editing for blog content powered by Gemini via MCP. Claude acts as Creative Director - interpreting intent, selecting domain expertise, constructing optimized 6-component prompts (Subject + Action + Context + Composition + Lighting + Style), and orchestrating Gemini for blog-quality results. Generates hero images, inline illustrations, social preview cards, and OG images. Edits existing blog images. Supports 6 blog-optimized domain modes (Editorial, Product, Landscape, UI/Web, Infographic, Abstract). Works standalone via /blog image or internally from blog-write and blog-rewrite workflows. Falls back gracefully when MCP is not configured. Use when user says "blog image", "generate hero image", "blog illustration", "social card", "generate blog image", "edit blog image", "image generate", "blog cover image", "inline image", "OG image".

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 improve code — one skill, four modes: bug/security review (default), performance, clean-code audit, slop cleanup. Pass mode:review|perf|clean|cleanup or infer. Don't use for writing features or generating tests (use test-coverage).

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Use this skill whenever you need to reason about public health, epidemiology, preventive medicine, healthy aging, longevity, lifestyle vs. genetics, or dietary patterns. Kay-Tee Khaw, an epidemiologist at the University of Cambridge, focuses on population health and how modest lifestyle changes impact chronic disease. Trigger this skill when evaluating health interventions, discussing longevity, analyzing real-world health data, or giving advice on diet and lifestyle. Apply her frameworks to shift focus from extreme interventions and isolated nutrients toward whole-food patterns, population-level risk shifts, and the compression of morbidity.

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-assisted pair programming with multiple modes (driver/navigator/switch), real-time verification, quality monitoring, and comprehensive testing. Supports TDD, debugging, refactoring, and learning sessions. Features automatic role switching, continuous code review, security scanning, and performance optimization with truth-score verification.

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。

Generate North American road-trip itineraries as a map-first, offline-friendly single-file HTML page. Plans around daily driving segments, overnight stops, fuel/EV-charging, national-park reservations (Recreation.gov / NPS), seasonal road closures, and timezone/border crossings — for executable, decision-ready trips. Two entry modes: give a start + region/destination + days and it plans the whole route, or hand it an existing route and it verifies, fills gaps, and produces the page.

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 applications with React Router in Framework, Data, Declarative, and unstable RSC modes. Use when configuring routes, route modules, loaders, actions, forms, fetchers, navigation, pending UI, SSR/SPA/pre-rendering, middleware, URL params/search params, or React Router upgrades.

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 single config quality skill. Two modes: (1) Default — review/wire pending self-improvement proposals. (2) Audit — analyzes skills, rules, CLAUDE.md, project refs, hooks, and agents against the actual codebase to find inaccuracies, trigger overlaps, stale references, and weak rules, then fixes them. Trigger on 'self-evolve', 'evolve', 'config health check', 'audit config', 'check claude setup', 'apply this rule', 'reorganize rules', 'ok' (when proposals are pending). NOT for improving individual skills (use skill-creator), diagnosing code bugs (use diagnose), or fixing broken code (use 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。

Use this skill when simulating vehicle motion, calculating safe following distances, time-to-collision, speed/position updates, or implementing vehicle state machines for cruise control modes.

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。

Run Neo4j Graph Analytics algorithms (PageRank, Louvain, WCC, Dijkstra, KNN, Node2Vec, FastRP, GraphSAGE) directly inside Snowflake without moving data. Use when running graph algorithms against Snowflake tables via the Neo4j Snowflake Native App ("GDS Snowflake", "graph algorithms in Snowflake", "Neo4j Graph Analytics"). Covers the explore → prepare projection views → project-compute-write flow, the strict view/column type rules the graph engine requires, exact SQL CALL syntax, and privilege setup in both modes — app-identity grants and execute-as-user / per-user PAT auth (programmatic access token, set_enable_custom_credentials, register_user_role, caller grants). Does NOT cover Cypher or Neo4j DBMS queries — use neo4j-cypher-skill. Does NOT cover Aura Graph Analytics — use neo4j-aura-graph-analytics-skill. Does NOT cover self-managed GDS — use neo4j-gds-skill.

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。

Neo4j Graph Data Science (GDS) embedded plugin via Python client or Cypher — covers graphdatascience client 2.x, GraphDataScience, gds.graph.project.native, gds.graph.project.cypher, snake_case endpoints, graph catalog operations, stream/stats/mutate/write modes, memory estimation, PageRank, Louvain, WCC, FastRP, KNN, Node Similarity, ML pipelines, and cleanup. Use for Aura Pro, self-managed, local, or offline Neo4j DBMS with the GDS plugin installed. Does NOT cover Aura Graph Analytics GDS Sessions, AuraGraphDataScience, GdsSessions, gds.graph.project.remote, or AuraDB Cypher API projection/session management — use neo4j-aura-graph-analytics-skill. Does NOT handle Cypher authoring — use neo4j-cypher-skill. Does NOT cover driver setup — use neo4j-driver-python-skill or other driver skill.

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。

Import structured data into Neo4j — LOAD CSV, CALL IN TRANSACTIONS, neo4j-admin database import full (offline bulk), apoc.load.csv/json, apoc.periodic.iterate, driver batch writes. Covers method selection, header file format, type coercion, null handling, ON ERROR modes, CONCURRENT TRANSACTIONS, pre-import constraint setup, and post-import validation. Use when importing CSV/JSON/Parquet files, migrating relational data to graph, or bulk-loading large datasets. Does NOT handle unstructured document/PDF/vector chunking pipelines — use neo4j-document-import-skill. Does NOT handle live app write patterns (MERGE/CREATE) — use neo4j-cypher-skill. Does NOT handle neo4j-admin backup/restore/config — use neo4j-cli-tools-skill.

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。