「engine」の検索結果

Resilience testing specialist for failure injection, game day planning, and building confidence in system reliabilityUse when "chaos engineering, resilience testing, failure injection, game day, fault tolerance, chaos experiment, disaster recovery, reliability testing, chaos-engineering, resilience, failure-injection, game-day, fault-tolerance, reliability, testing, litmus, chaos-monkey, ml-memory" mentioned.

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。

Routes to the right vibe-engineering skill for the current task and lists the full catalog. Use when the user asks which skill to use, asks what vibe-engineering can do, or is unsure how to approach a task.

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-engineer workflow skill. Use this skill when the user needs Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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。

SEO 专家 (SEO (search engine optimization)) Master OS — automated mastery of SEO (search engine optimization): top builders' mental models, tool stack, current workflows, jargon, and where to keep up. Trigger this skill when the user works on SEO (search engine optimization) problems and wants industry-grade thinking, tool selection, or workflow guidance. 触发词：「SEO」「搜索引擎优化」「排名」「外链」「页面优化」

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。

产品设计 / UX 设计 (产品设计 / UX 设计 (Product Design / UX Design) — 数字产品的用户体验设计：从用户研究 → 信息架构 → 交互设计 → 视觉/UI → 可用性测试 → 设计系统的认知操作系统，面向 UX designer / product designer / interaction designer / UX researcher / design systems engineer / design lead，以及想入行、转岗、服务这行(设计外包、设计工具厂商、研究平台)的视角。覆盖: (a) 第一性张力 — **用户中心/研究驱动 (user-centered, 'you are not the user', research before pixels, observe behavior not opinions) ⇄ 商业目标/约束/交付 (business goals, north-star metrics, ship it, designer 服务于产品成功不是个人作品集)**; **设计直觉/品味/craft (taste, aesthetics, 'attractive things work better' — Norman 情感化设计) ⇄ 数据/实验/A-B 测试 (data-driven, metrics, experimentation, 'opinions are not data')**; **用户说的 (stated preference, 访谈里说喜欢) ⇄ 用户做的 (revealed behavior, 行为观察 > 自陈, usability test 看人真实卡在哪)**; **一致性/设计系统/规范 (consistency, design system, Jakob's law 用户带着别处的习惯来, 复用组件) ⇄ 创新/打破模式 (innovation, 该不该破规范)**; **减法/简化 (simplicity, Krug 'Don't Make Me Think', less but better — Dieter Rams) ⇄ 功能丰富/利益相关者塞需求 (feature creep, stakeholder pressure)**; **UX(体验/流程/研究) ⇄ UI(视觉/像素/组件)** 的职责之争, **designer 该不该写代码 (design engineer / 'should designers code')**; (b) 核心工作流 / pipeline (最标准、最易蒸高质量+CLI 化) — Double Diamond (发现 discover → 定义 define → 开发 develop → 交付 deliver) / Design Thinking (共情 empathize → 定义 → 构思 ideate → 原型 prototype → 测试 test) / Design Sprint (Jake Knapp 5 天冲刺); 完整链: 用户研究 (访谈/问卷/可用性测试/卡片分类) → persona / journey map / JTBD → 信息架构 IA + 用户流 user flow → 线框 wireframe (低保真) → 交互/原型 prototype (高保真) → 视觉 UI / 设计系统落地 → 可用性测试 usability testing → handoff 给开发 → 度量迭代 (北极星 / HEART 框架); (c) 工具栈 — 设计/原型 (Figma 绝对主导 / Sketch 衰退 / Adobe XD 已停更 / Framer 高保真+建站 / Penpot 开源 / Principle / ProtoPie 微交互); 协作白板 (FigJam / Miro / Mural); 用户研究 (Maze / UserTesting / Lookback / Dovetail 研究库 / Optimal Workshop 卡片分类树测试 / Hotjar / Microsoft Clarity 热图); 设计系统/交付 (Storybook / 蓝湖(中) / Zeplin / design tokens / Tokens Studio); 度量 (Amplitude / Mixpanel / 北极星指标); AI 新兴 (Figma AI / v0 by Vercel / Galileo AI / Uizard / Cursor 给 design engineer); (d) 知识正典 — Don Norman《The Design of Everyday Things》(affordance/signifier/mapping 圣经)、Steve Krug《Don't Make Me Think》(可用性入门)、Alan Cooper《About Face》《The Inmates Are Running the Asylum》(交互设计/persona 起源)、Jakob Nielsen 10 Usability Heuristics + NN/g 文章库、Jake Knapp《Sprint》、Jeff Gothelf《Lean UX》、Teresa Torres《Continuous Discovery Habits》、Erika Hall《Just Enough Research》、Julie Zhuo《The Making of a Manager》、《Refactoring UI》(Adam Wathan/Steve Schoger)、《Universal Principles of Design》、Laws of UX (Jon Yablonski)、《100 Things Every Designer Needs to Know About People》(Susan Weinschenk)、IDEO/Stanford d.school 设计思维材料; (e) figures/流派 — 认知心理/人因派 (Don Norman 认知科学奠基、Susan Weinschenk 行为心理、Kathryn Whitenton); 可用性工程派 (Jakob Nielsen 启发式/折扣可用性、Steve Krug、Jared Spool UIE); 交互设计/目标导向派 (Alan Cooper goal-directed/persona、Kim Goodwin); 设计思维派 (IDEO Tim Brown、David Kelley d.school); 精益/持续探索派 (Jeff Gothelf Lean UX、Teresa Torres continuous discovery、Marty Cagan《Inspired》产品发现); 设计系统/系统化派 (Brad Frost Atomic Design、Nathan Curtis design tokens、Alla Kholmatova); 视觉/UI craft 派 (Adam Wathan & Steve Schoger Refactoring UI、Dieter Rams 'less but better' 工业设计遗产); 设计领导/职业派 (Julie Zhuo、Aarron Walter 情感化设计、John Maeda); 移动优先 (Luke Wroblewski 'Mobile First'); (f) 行业话术/黑话 — affordance 可供性 / signifier 意符 / mental model 心智模型 / IA 信息架构 / heuristic evaluation 启发式评估 / usability 可用性 / a11y accessibility 无障碍 / WCAG / persona 用户画像 / journey map 用户旅程 / JTBD jobs-to-be-done / north-star metric 北极星 / HEART 框架 / wireframe 线框 / mockup / prototype 原型 / fidelity 保真度 (lo-fi/hi-fi) / design system 设计系统 / design token 设计令牌 / atomic design 原子设计 / component library 组件库 / handoff 交付 / red routes 关键路径 / dark pattern 暗黑模式 / Fitts's law / Hick's law / Jakob's law / Miller 7±2 / progressive disclosure 渐进披露 / above the fold / hamburger menu / skeuomorphism vs flat / micro-interaction / empty state / edge case / happy path / design debt 设计债 / dogfooding / dot voting / affinity mapping 亲和图 / card sorting 卡片分类 / tree testing / A/B test / NPS / SUS (System Usability Scale); (

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。

UBNT/UniFi 企业 Wi-Fi 工程 (UniFi/UBNT Enterprise Wi-Fi Engineering) Master OS — automated mastery of UniFi/UBNT Enterprise Wi-Fi Engineering: top builders' mental models, tool stack, current workflows, jargon, and where to keep up. Trigger this skill when the user works on UniFi/UBNT Enterprise Wi-Fi Engineering problems and wants industry-grade thinking, tool selection, or workflow guidance. 触发词：「造大师 UBNT Wi-Fi」「UBNT WiFi 工程」「UniFi 高密度部署」「我做企业 Wi-Fi」「80 人办公网慢」

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。

Figma 转 Photoshop (PSD) (Figma → Photoshop (PSD) 设计稿转换 (从业者视角) — 把 Figma 设计文件高保真转换为 Photoshop 分层 PSD, 核心是对齐两个工具的概念/渲染差异, 让产出的设计稿视觉一致. 覆盖: (a) 概念映射 — Figma frame / auto-layout / component / variant / constraint / vector-network / boolean / effect (drop·inner shadow / layer·background blur) / mask / blend mode / gradient / text-engine / color 与 Photoshop artboard / group / smart-object / linked / layer-style / shape-layer / path / clipping·layer mask / blend-mode 的对应关系与不可逆损耗点; (b) 转换方法栈 — 插件直出 PSD / 导出图层 (PNG·SVG) 再重组 / SVG·PDF 桥接 / 手工重建 / Figma REST API + Photoshop UXP·ExtendScript 脚本化, 各法在保真度-可编辑性-工时上的权衡与选型; (c) 保真度 QA — 字体回退与缺字处理 / 颜色空间 (sRGB·ICC profile) / 效果参数对齐 / @Nx·DPI 与栅格化 / 像素 diff 验收; (d) 两种交付目标 — 可编辑分层 PSD vs 像素保真扁平 PSD 的方法选择. 主战场 = Figma Community 插件 + Adobe 官方文档/论坛 + 设计交付 (design handoff) 实践 + 设计师社区. 不含: PSD→Figma 反向转换 / Sketch / Adobe XD / 纯前端 code handoff (HTML·CSS) / 印刷 CMYK 专业制版 (仅触及).) Master OS — automated mastery of Figma → Photoshop (PSD) 设计稿转换 (从业者视角) — 把 Figma 设计文件高保真转换为 Photoshop 分层 PSD, 核心是对齐两个工具的概念/渲染差异, 让产出的设计稿视觉一致. 覆盖: (a) 概念映射 — Figma frame / auto-layout / component / variant / constraint / vector-network / boolean / effect (drop·inner shadow / layer·background blur) / mask / blend mode / gradient / text-engine / color 与 Photoshop artboard / group / smart-object / linked / layer-style / shape-layer / path / clipping·layer mask / blend-mode 的对应关系与不可逆损耗点; (b) 转换方法栈 — 插件直出 PSD / 导出图层 (PNG·SVG) 再重组 / SVG·PDF 桥接 / 手工重建 / Figma REST API + Photoshop UXP·ExtendScript 脚本化, 各法在保真度-可编辑性-工时上的权衡与选型; (c) 保真度 QA — 字体回退与缺字处理 / 颜色空间 (sRGB·ICC profile) / 效果参数对齐 / @Nx·DPI 与栅格化 / 像素 diff 验收; (d) 两种交付目标 — 可编辑分层 PSD vs 像素保真扁平 PSD 的方法选择. 主战场 = Figma Community 插件 + Adobe 官方文档/论坛 + 设计交付 (design handoff) 实践 + 设计师社区. 不含: PSD→Figma 反向转换 / Sketch / Adobe XD / 纯前端 code handoff (HTML·CSS) / 印刷 CMYK 专业制版 (仅触及).: top builders' mental models, tool stack, current workflows, jargon, and where to keep up. Trigger this skill when the user works on Figma → Photoshop (PSD) 设计稿转换 (从业者视角) — 把 Figma 设计文件高保真转换为 Photoshop 分层 PSD, 核心是对齐两个工具的概念/渲染差异, 让产出的设计稿视觉一致. 覆盖: (a) 概念映射 — Figma frame / auto-layout / component / variant / constraint / vector-network / boolean / effect (drop·inner shadow / layer·background blur) / mask / blend mode / gradient / text-engine / color 与 Photoshop artboard / group / smart-object / linked / layer-style / shape-layer / path / clipping·layer mask / blend-mode 的对应关系与不可逆损耗点; (b) 转换方法栈 — 插件直出 PSD / 导出图层 (PNG·SVG) 再重组 / SVG·PDF 桥接 / 手工重建 / Figma REST API + Photoshop UXP·ExtendScript 脚本化, 各法在保真度-可编辑性-工时上的权衡与选型; (c) 保真度 QA — 字体回退与缺字处理 / 颜色空间 (sRGB·ICC profile) / 效果参数对齐 / @Nx·DPI 与栅格化 / 像素 diff 验收; (d) 两种交付目标 — 可编辑分层 PSD vs 像素保真扁平 PSD 的方法选择. 主战场 = Figma Community 插件 + Adobe 官方文档/论坛 + 设计交付 (design handoff) 实践 + 设计师社区. 不含: PSD→Figma 反向转换 / Sketch / Adobe XD / 纯前端 code handoff (HTML·CSS) / 印刷 CMYK 专业制版 (仅触及). problems and wants industry-grade thinking, tool selection, or workflow guidance. 触发词：「figma 转 psd」「figma to psd」「figma 转 photoshop」「figma 导出 psd」「设计稿转换」

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。

Suede-affiliated AI search optimization discipline. Use when the user wants to optimize content for AI search engines, get cited by LLMs, or appear in AI-generated answers. Also use when the user mentions 'AI SEO,' 'AEO,' 'GEO,' 'LLMO,' 'answer engine optimization,' 'generative engine optimization,' 'LLM optimization,' 'AI Overviews,' 'optimize for ChatGPT,' 'optimize for Perplexity,' 'AI citations,' 'AI visibility,' 'zero-click search,' 'how do I show up in AI answers,' 'LLM mentions,' 'optimize for Claude/Gemini,' 'llms.txt,' 'OKF,' 'Open Knowledge Format,' 'knowledge bundle,' or 'agent-readable site.' The durable job: make content structurally extractable, citable, and agent-readable so AI systems surface and cite it. NOT FOR: traditional technical SEO audit (use suede-seo-audit) or launch-appeal grading (use suede-visibility-grader).

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。

SEO + Generative Engine Optimization (GEO) for 2026 — technical SEO, on-page optimization, structured data (JSON-LD, schema.org), Core Web Vitals, citability scoring (llms.txt, entity clarity), AI search engine optimization (ChatGPT, Gemini, Perplexity, Claude, Google AI Overviews), and brand authority building. Use when user asks to optimize a site for search engines, improve SEO, write SEO content, implement structured data, optimize for AI search/GEO, audit a page, or improve Google rankings. Do NOT use for content writing strategy (use content-marketing), performance optimization beyond Core Web Vitals (use performance-profiler), or paid ad 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。

Guided, section-by-section authoring of the master architecture document for the game. Reads all GDDs, the systems index, existing ADRs, and the engine reference library to produce a complete architecture blueprint before any code is written. Engine-version-aware: flags knowledge gaps and validates decisions against the pinned engine version.

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。

Code review focused exclusively on over-engineering. Finds what to delete: reinvented standard library, unneeded dependencies, speculative abstractions, dead flexibility. One line per finding: location, what to cut, what replaces it. Use when the user says "review for over-engineering", "what can we delete", "is this over-engineered", "simplify review", or invokes /ponytail-review. Complements correctness-focused review, this one only hunts complexity.

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。

Web search, online retrieval, real-time information query, search engine search, Reddit and other community platform discussions, external site posts and trending topics. Trigger when users need to search for the latest information online, look up recent news or trends, query real-time data, research topics via search engines, browse Reddit or community discussions, discover external site posts and trending topics, obtain any online content, web search, online lookup, real-time information, news search, Reddit, trending topics, search engine. Even if the user does not explicitly say "search", trigger this skill whenever their intent involves obtaining real-time web information or verifying current facts.

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。

Orchestrate evidence-first engineering for WeChat and other mini programs from a vague idea or existing repository through project discovery, product specification, architecture, implementation, debugging, device adaptation, verification, and release readiness. Use when users ask to build a mini program from zero to one, take over an existing mini-program project, deliver a cross-stage feature, diagnose project status, coordinate development and testing, or judge whether a mini program is ready to upload or release. Enforces fact discovery, change boundaries, stage gates, evidence-calibrated status, sensitive-information redaction, and continuity after side questions.

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 product brief is finalized and ready to hand off to the engineering team, or when asked to send a brief to Apex, kick off engineering work, or start development on a product spec. Examples: "hand this off to engineering", "send brief to Apex", "start building this", "kick off dev on this spec".

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 existing resilience — identify untested failure modes and chaos engineering gaps. Use when asked "how resilient are we", "what failure modes are untested", or "find our chaos engineering gaps".

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。

ML/AI engineer — LLM integrations, prompt engineering, model pipelines, evals, RAG. Use when asked to "add AI to this", "integrate an LLM", "build a RAG pipeline", "evaluate model accuracy", or "improve this prompt".

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 onboarding documentation — what this project does, how to set up locally, where things live, key decisions, how to deploy. Written for day-one engineers who know nothing. Use when asked for "onboarding docs", "new engineer guide", "how to get started", or "developer setup".

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。

Provides chaos engineering best practices for resilience testing, fault injection, and game day planning. Use when designing resilience experiments, configuring chaos tools, planning game days, or when user mentions 'chaos engineering', 'resilience', 'litmus', 'game day', 'fault injection', 'chaos monkey', 'blast radius', 'steady state', 'failure 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。

Systems engineering covering requirements management, the V-model lifecycle, integration planning, verification and validation (V&V), interface control, trade studies, and the NASA Systems Engineering Handbook. Spans the full lifecycle from concept through operations and disposal. Includes requirements decomposition, traceability matrices, configuration management, and technical performance measures. Use when managing complex system development, writing requirements, planning integration, or conducting V&V activities.

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 engineering-standard drawings (P&ID, SLD, floor plans, isometric) with ISA-5.1 and IEEE symbol libraries in SVG/DXF format. Activates for drawing generation, diagram creation, blueprint packaging, and output formatting from verified engineering calculations.

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。

Transition from a hands-on "bricklayer" to a high-level "architect" by managing a fleet of autonomous AI agents. Use this when you need to scale engineering output with a small team, handle repetitive migrations/bug fixes, or onboard engineers to complex legacy codebases.

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 whenever the user wants to find, shortlist, vet, or enrich US software development firms — custom software, web development, mobile app development, backend/API development, DevOps/cloud, system integration, and hosting. Triggers on "find a software dev shop in Austin", "shortlist three custom-software firms with healthcare experience", "we need a mobile app developer for our iOS launch", or "pull contact info for these 10 dev shop domains", even when described indirectly (build a tool, ship a feature, technical partner). Drives the ServiceGraph API (api.servicegraph.co) — a 100k+ US firm catalog filterable by industry, services, location, size, ratings. Defer to find-web-developer for strictly website/landing-page projects. Defer AI/ML, ML pipelines, model building, and data-engineering asks — those are a sibling industry, not software development. Skip in-house engineer hires, code-writing/debugging tasks, cloud-product comparisons, hardware/civil engineering, non-US firms, individual freelancers.

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。

游戏安全逆向专项。当任务涉及游戏反作弊分析、Unity/UE 逆向、内存扫描、DBI 框架、IL2CPP 分析、 游戏保护壳（VMProtect/Themida）脱壳、Cheat Engine、游戏 Mod 开发时使用本 skill。 触发关键词：游戏逆向、反作弊、Cheat Engine、Unity、IL2CPP、Unreal Engine、x64dbg、游戏安全、 game hacking、anti-cheat、EAC、BattlEye、Vanguard。

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。

[Deprecated] engineering bridge merged. Use `cm-mcp-engineering` instead.

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。