182 件 ・ 関連度順
概要と使いどころ
Production guidance for converting sourced data and approved claims into truthful, accessible, deterministic animated visualizations with D3. Use for data-driven charts, maps, networks, hierarchies, transitions, annotations, responsive video variants, frame-by-frame browser rendering, and visualization QA; not for generic dashboards, unsourced decorative charts, or ordinary motion graphics without a data contract.
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 Cypress test suites in TypeScript: E2E tests, component tests, custom commands, cy.intercept network control, cy.session login, Cypress Cloud, and CI integration. Covers retry-ability, the command queue, cross-origin flows with cy.origin, and data-driven testing with fixtures. Use when: "write E2E test in Cypress," "Cypress page object / custom command," "cy.," "cy.intercept," "Cypress component test," "Cypress Cloud," "cypress.config.ts." Not for: Playwright suites — use playwright-automation; flaky-test healing or quarantine — use test-reliability; bulk selector regeneration after a UI refactor — use selector-drift-recovery; Selenium-to-Cypress conversion — use test-migration. Related: playwright-automation, ci-cd-integration, visual-testing, unit-testing, test-reliability.
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。
Creates interactive data visualizations with Apache ECharts, the open-source JavaScript charting library. Use when a user asks to build charts, dashboards, or data-driven graphics using ECharts in React, Vue, or vanilla JavaScript applications, render a chart to SVG on the server, or upgrade from ECharts 5 to 6.
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。
You are an expert in Clay, the data enrichment and outbound sales platform that pulls from 75+ data providers to build rich prospect profiles. You help teams automate lead discovery, enrich contacts with firmographic and technographic data, score leads against ICP criteria, and trigger personalized outreach sequences — replacing manual research with automated, data-driven prospecting.
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。
Automate Adobe After Effects workflows. Use when a user asks to script After Effects with ExtendScript or CEP, batch render compositions, automate motion graphics templates (MOGRTs), build render pipelines with aerender, create expressions for animations, manage project files programmatically, automate text and image replacements in templates, build data-driven motion graphics, integrate After Effects with CI/CD, or control AE via command line. Covers ExtendScript, CEP panels, expressions, aerender CLI, and template automation.
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。
World-class marketing expertise combining Seth Godin's permission marketing philosophy, Neil Patel's data-driven growth tactics, and the strategic frameworks from brands like Apple, Nike, and Dollar Shave Club. Marketing is the art and science of creating customers. Great marketing isn't about shouting louder - it's about being more relevant. The best marketers understand that attention is earned, not bought. They build systems that compound, create word-of-mouth, and turn customers into advocates. Marketing is the bridge between what you've built and the people who need it. Use when "marketing, campaign, go-to-market, gtm, launch, promotion, advertising, ads, acquisition, demand gen, lead gen, channel, funnel, conversion, cac, customer acquisition, reach, awareness, consideration, marketing, advertising, acquisition, campaigns, gtm, demand-generation, analytics, channels" 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。
Master the AI tools that transform financial operations. From bookkeeping to forecasting, manage money smarter and make data-driven financial decisions. Use when "finance, accounting, budgeting, forecasting, FP&A, bookkeeping, expense management, finance, accounting, budgeting, forecasting, fpa, expenses" 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。
World-class content strategy expertise combining the frameworks of Andy Crestodina's data-driven approach, Ann Handley's "everybody writes" philosophy, and the content engines that power companies like HubSpot, Ahrefs, and Intercom. Content strategy isn't about creating content - it's about creating the right content for the right audience at the right time in the right format. The best content strategists think in systems, not pieces. They build content engines that compound over time and turn strangers into customers and customers into advocates. Use when "content strategy, content plan, editorial calendar, blog strategy, content marketing, topic clusters, pillar content, content audit, content calendar, SEO content, content distribution, content funnel, thought leadership, content engine, content topics, what to write, content, strategy, editorial, SEO, blog, planning, distribution, measurement" 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。
The practice of collecting, analyzing, and acting on data to drive product decisions. Great analytics isn't about dashboards—it's about insights that lead to action. Every metric should answer a question that changes behavior. This skill covers event tracking, metrics design, dashboards, user behavior analysis, and data-driven decision making. The best analytics teams measure what matters, not what's easy to measure. Use when "analytics, metrics, tracking, dashboard, funnel, cohort, retention, events, KPI, measure, data, insights, conversion, engagement, analytics, metrics, data, dashboards, tracking, funnels, cohorts, KPIs, insights" 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。
World-class expertise in measuring, attributing, and optimizing AI-generated content performance. Combining data science rigor with content strategy intelligence to answer the questions traditional content analytics can't: Is AI content performing? Which AI variations convert? What's the true ROI of AI vs traditional content creation? This isn't vanity metrics for robots. This is the discipline of proving AI content drives business outcomes - and using that data to make AI content systems better, faster, and more profitable. Built on the principles of companies like Jasper, Copy.ai, and Notion who've scaled AI content operations with measurement as the foundation. Use when "ai content performance, ai content analytics, measure ai content, ai content roi, ai vs human content, ai content attribution, ai content testing, ai variation testing, ai content dashboard, ai content metrics, prompt performance, ai content conversion, ai content quality score, content velocity, ai content efficiency, ai-content, analytics, measurement, attribution, roi, ab-testing, performance, optimization, data-driven, content-analytics" 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。
Analyze Google Analytics data, review website performance metrics, identify traffic patterns, and suggest data-driven improvements. Use when the user asks about analytics, website metrics, traffic analysis, conversion rates, user behavior, or performance optimization.
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。
Template-based page generation at scale for SEO. Data-driven content, internal linking architecture, and automated optimization for large-scale content operations. Use when the user asks about programmatic SEO, pSEO, scaled content, template pages, or automated page 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。
千瓜数据创始团队视角. 数据驱动派代表方法论 + 工具派. 调用此 skill 时, 用千瓜的认知框架做小红书数据 / 选题 / 投放决策.
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。
UX research and design toolkit for Senior UX Designer/Researcher including data-driven persona generation, journey mapping, usability testing frameworks, and research synthesis. Use when conducting user research, creating personas, mapping user journeys, planning usability tests, or validating designs.
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。
Programmatic SEO planning and analysis for pages generated at scale from data sources. Covers template engines, URL patterns, internal linking automation, thin content safeguards, and index bloat prevention. Use when user says "programmatic SEO", "pages at scale", "dynamic pages", "template pages", "generated pages", or "data-driven SEO".
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。
When the user wants to create SEO-driven pages at scale using templates and data. Also use when the user mentions "programmatic SEO," "template pages," "pages at scale," "directory pages," "location pages," "[keyword] + [city] pages," "comparison pages," "integration pages," "building many pages for SEO," "pSEO," "generate 100 pages," "data-driven pages," or "templated landing pages." Use this whenever someone wants to create many similar pages targeting different keywords or locations. For auditing existing SEO issues, see seo-audit. For content strategy planning, see content-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。
Applies the reasoning of Pieter Abbeel, robotics and reinforcement learning expert, UC Berkeley professor, and co-founder of Covariant. Use this skill whenever you are designing AI systems, tackling Sim2Real transfer, deploying machine learning in the physical world, or evaluating reinforcement learning architectures. Trigger this skill for questions about domain randomization, reward design, bootstrapping real-world AI, robotics hardware assumptions, or shifting from hard-coded rules to data-driven deep learning. It helps ground theoretical AI in physical embodiment and pragmatic deployment.
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 to reason like Martin Heidegger, 20th-century German philosopher and author of Being and Time. Reach for this skill whenever you encounter discussions about the existential impact of technology, human meaning-making, mortality, or the limits of purely scientific and data-driven worldviews. Trigger this skill even if the user doesn't name Heidegger, especially when they are trapped in instrumental thinking, treating themselves or others as mere resources, or struggling with authenticity and societal expectations. Apply his frameworks to shift the AI's perspective from detached, objective observation to embedded, practical engagement with the world.
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。
Patterns for Rust testing in Axone CosmWasm contracts. Use when adding unit tests, integration tests, data-driven cases, or coverage-oriented test scenarios.
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。
This skill should be used when the user asks to "make a video with Remotion", "create a programmatic/data-driven video in React", "render an MP4/GIF from code", "animate with useCurrentFrame/interpolate/spring", "sync video to audio/beats", or "render a templated video per record headlessly". Covers building React compositions and rendering them via CLI or @remotion/renderer.
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 or changing tuning values, items, enemies, abilities or levels - put them in the engine's data assets (ScriptableObject, Resource, DataAsset/DataTable, JSON/RON) with validation and stable IDs, keep runtime state out of shared data, inject services instead of singletons, and test data invariants.
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, curate, and grow email newsletters across all formats and strategies. Use when working on newsletters, email newsletters, weekly digests, link roundups, curated content, audience building, subscriber engagement, or content distribution. Covers 6 newsletter formats (curated/link roundup, story-driven, educational, interview, data-driven, personal update), editorial issue structure, content sourcing workflows, commentary writing, sending cadence, subject line optimization, subscriber growth, and engagement metrics. Trigger keywords: newsletter curation, curated newsletter, newsletter writing, newsletter format, newsletter strategy, newsletter template, content curation, subscriber growth.
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。
Transform raw data from CSVs, Google Sheets, or databases into executive-ready reports with visualizations, key metrics, trend analysis, and actionable recommendations. Creates data-driven narratives for leadership. Use when users need to turn spreadsheets into executive summaries or board reports.
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。