136 件 ・ 関連度順
概要と使いどころ
Full-spectrum product research pipeline. Runs competitive analysis, technology trend scouting, user feedback analysis, and feature ideation. Trigger on: research, competitive research, market research, feature discovery, what should we build next, technology trends, user feedback, app store reviews, GitHub issues analysis, competitive landscape, product 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。
Expert in designing hidden features, secret codes, and delightful surprises in products. Covers discovery mechanics, reward calibration, shareability triggers, and maintaining the magic. Knows how to create moments that make users feel special for finding them. Use when "easter egg, hidden feature, secret code, surprise and delight, konami code, hidden message, secret mode, " 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。
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。
Build an Opportunity Solution Tree (OST) to structure product discovery — map a desired outcome to customer opportunities, possible solutions, and experiments. Based on Teresa Torres' Continuous Discovery Habits. Use when the team is unclear what to build next, when multiple opportunities compete, or before writing a PRD for a complex feature space.
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。
Plan the UX and UI for a feature before writing code. Run a structured discovery interview, then produce a design brief (.design-context.md) that guides implementation. Establishes design direction, constraints, and strategy before any code is written. Triggers on plan the design, design brief, shape the UX, before we build, design discovery.
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。
Universal SDLC pipeline orchestrator with stack provider auto-discovery. Reads stack.md profiles from installed plugins, picks the highest-priority match, executes a 5-phase pipeline (BA → Dev → QA → Sec → Docs) plus stack-defined extra phases. Use when: - User invokes /sdlc:start "<feature>" - User asks to "run the SDLC pipeline" or "go through the full pipeline" - You need to coordinate specialist agents to deliver a complete feature Do NOT use for: - Trivial single-file edits (just edit directly) - Read-only questions about the codebase - Casual conversation
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。
Phase 0 validation gate — problem framing, competitive analysis, feasibility, and a go/no-go checkpoint before committing to a feature. Use when evaluating whether an idea is worth building, before /story or /design. Trigger on "is this worth building", "validate this idea", "discovery", "should we build".
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。
Orchestrates 6-phase SDLC pipeline (discovery, requirements, architecture, workstreams, implementation, summary) for guided feature development. Use when user runs /core:develop command, requests spec-driven development, wants to create implementation plans with architecture decisions, or mentions "SDLC", "spec-driven", "plan feature", "development pipeline". Supports plan persistence, wave-based resume, autonomous mode, and architecture/implementation 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。
Autonomous competitive analysis and feature discovery pipeline. Runs /compete and /new-features on each project, produces actionable market positioning insights. Schedule daily or weekly.
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。
Full-spectrum product research pipeline. Runs competitive analysis, technology trend scouting, user feedback analysis, and feature ideation. Triggers: on: research, competitive research, market research, feature discovery, what should we build next.
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。
Produces a DRAFT product requirements document from the discovery notes, interview summaries, support themes, analytics notes and stakeholder messages the user provides: problem statement, target users, goals with measures as stated, numbered requirements each with a testable acceptance criterion, non-goals, constraints, dependencies and open questions, with every statement tagged evidenced, assumed or UNKNOWN so each assumption is visible for the product owner to confirm. Use when the user asks to "write a PRD", "draft the product requirements", "turn these discovery notes into requirements", "document what this feature needs to do" or "build the requirements doc for this epic". Do not use for supplier-facing requirements in a tender, use rfp-requirements-pack instead; for a technical design decision, use architecture-decision-record; for the change ticket that ships the work, use change-request-pack. Drafts for human review; never approves, authorises or signs 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。
web アプリの機能を構造化して書き下すワークフロー。新規/既存の 2 モード、5 フェーズで構造化（先行事例調査は並列3エージェント、Reader Test 付き）。「機能を考えたい」「機能定義したい」「web アプリ作りたい」「機能から設計したい」「新しい機能」で発動。※ 曖昧な状態の掘り下げは deep-interview、要件統合は discovery-council、設計は design を使う。
Implement, review, or improve in-app tips and onboarding using Apple's TipKit framework. Use when adding feature discovery tooltips, onboarding flows, contextual tips, first-run experiences, coach marks, or working with Tip protocol, TipView, popoverTip, tip rules, tip events, or feature education UI.
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。
Explains ML predictions on omics data with SHAP, LIME, and permutation importance, handling the correlated-feature trap, the conditional-vs-interventional Shapley choice, and the attribution-is-not-causation boundary. Use when interpreting an omics classifier, debugging shortcut/batch learning, or deciding whether an attribution ranking can be trusted as biology. For validated feature selection see machine-learning/biomarker-discovery; explanations are not a selection method.
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。
Selects biomarker features from high-dimensional omics data using Boruta all-relevant selection, mRMR, LASSO/elastic-net, and stability selection, while controlling the leakage, irreproducibility, and correlated-feature traps that make most published signatures fail to replicate. Use when identifying candidate biomarkers, deciding between an all-relevant and a minimal-optimal selector, or judging whether a selected gene set is reproducible. For unbiased performance estimation of the resulting model see machine-learning/model-validation; for interpreting a trained model see machine-learning/prediction-explanation.
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 diagnostic and prognostic classifiers on omics feature matrices with regularized logistic regression, random forest, and gradient-boosted trees, handling the p>>n regime, batch shortcut learning, class imbalance, and probability calibration. Use when building a classifier from expression, methylation, or variant data, choosing an algorithm for high-dimensional small-n data, or diagnosing a suspiciously perfect AUC. For unbiased evaluation see machine-learning/model-validation; for feature selection see machine-learning/biomarker-discovery; for time-to-event outcomes see machine-learning/survival-analysis.
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。
Pipeline that turns a big system idea into briefs for an agent fleet. Use when Arman says 'let's plan out X', 'build or overhaul the X system', 'create the vision and plan for X', 'do the full discovery process', 'get this ready for a fleet', or 'do what we did for education', or when carrying forward a VISION, COMPETITIVE_INSIGHTS, roadmap, or briefs doc. NOT for one feature in a live system (use build-sub-feature).
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。
Index-based file discovery using ABOUTME headers. Use INSTEAD of grep or Explore agent when searching for files by purpose or feature. Faster and more accurate than scanning code. Invoke this skill when user asks "which files handle X", "where is Y implemented", or when you need to find files related to a feature or 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。
Audit or design server-side indexes, directories, reputations, or aggregates that are DERIVED from traffic a platform witnesses (chain heads, run verdicts, heartbeats, publish activity) so that consent gates the derivation, not merely the read: no shadow index over non-consenting principals, post-consent-only evidence windows, retention bounds and delete-propagation into derived rows, activity-oracle threat modeling, and audit-logged ranking discretion. Use when building a capability directory / whois from witnessed activity, a reputation ledger from settled outcomes, vitals aggregation across tenants, or any "the yellow pages can't lie because they index signatures" feature. Keywords: shadow index, derived index, consent gates derivation, activity oracle, phone book not a log, delist propagation, ranking weight audit, k-anonymous aggregate, subpoena surface. NOT for the consent-screen UX and scope-ladder mechanics themselves (use local-first-tenancy-boundary), reputation scoring math and Sybil economics (use agent-identity-continuity-reputation), or discovery-layer architecture L1/L2/L3 (use agent-discovery-directories-guilds).
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。
Laravel向けパッケージを機能や対応バージョンで探し、更新状況、健全性の評価、提供元の指標を確認します。導入前に候補の互換性や保守状況を見比べるスキルです。
Integrate Firecrawl `/search` into product code and agent workflows. Use when an app needs discovery before extraction, when the feature starts with a query instead of a URL, or when the system should search the web and optionally hydrate result content.
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 a detailed, phased implementation plan with documentation discovery. Use when asked to plan a feature, task, or multi-step implementation — especially before executing with do.
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 the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document this architecture", "onboard me to this repo", or "create codebase docs". Do not trigger for routine feature implementation, bug fixes, or narrow code edits unless the user asks for repository-level discovery.
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。