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概要と使いどころ
Market Research workflow skill. Use this skill when the user needs Analyze market conditions, geographic opportunities, pricing, consumer behavior, and product validation across Google Maps, Facebook, Instagram, Booking.com, and TripAdvisor and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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Computes a numeric or categorical answer to a quantitative data-science question by cleaning and analyzing local data files (CSV, Excel, TSV, and scientific formats .npz/.fits/.h5) with pandas, numpy, and scipy. Use whenever a task ships its own dataset (in whatever local directory it provides) and asks you to derive a value via statistical, geospatial, temporal, ratio, percentage, growth-rate, correlation, signal-processing, orbital, or forecasting analysis. Spans domains including archeology (demographics, paleoclimate proxies, radiocarbon dating, historical conflicts); biomedical/bioinformatics (tumor histology, genes, proteins, peptides, genomic variants); environmental (water quality, bacterial/Enterococcus exceedance, rainfall correlations, environmental justice); legal/consumer (fraud, identity theft, consumer complaints by state/metro); wildfire (incidents, causes, suppression costs, acres burned, fatalities, geospatial intersections); and astronomy/heliophysics/space weather (satellite telemetry TLE/Swarm/SP3, indices OMNI/GOES, solar activity, atmospheric density, orbital mechanics, forecasting).
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 strategic frameworks and mental models of Anne Wojcicki, co-founder and CEO of 23andMe. Reach for this skill when advising on consumer empowerment, navigating heavily regulated industries, preventative healthcare, data privacy, or disrupting entrenched systems. Use this when the user is dealing with misaligned industry incentives, facing regulatory hurdles, building a consumer-research flywheel, or managing a team through a post-launch 'trough of sorrow'. Apply her principles of 'speaking with data', treating users as partners, and pushing for decade-long systemic change from the outside.
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。
Comprehensive market research and analysis skill. Use when sizing markets, conducting competitive analysis, generating professional market research reports, analyzing consumer behavior, or identifying market opportunities. Activates for: market research, market analysis, market report, TAM SAM SOM, market sizing, industry analysis, market landscape, competitive landscape, market trends, consumer research, Porter's Five Forces, PESTLE, SWOT, BCG Matrix, McKinsey-style report, consulting report, market opportunity, industry report, due diligence, M&A analysis, GTM market analysis, product-market fit validation.
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 Overview (AI Mode) scraping via Google Search. Returns AI-summarized key points for a single keyword, ideal for deep research, technical Q&A, long-tail product selection, and cross-border consumer preference analysis using the latest web information. Single-round only; follow-ups require the agent to summarize context and issue a new request. Triggered by: Google AI, AI Overview, AI Mode, Google AI search, AI search, deep research, consumer preference analysis, web summary, long-tail product research, cross-border market insights.
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。
🇺🇸 Product Launch & Product Hunt #1 Playbook — Multi-channel launch timing and sequencing. T-14 warm-up → T-0 launch day → T+7 momentum. Hunter selection, maker comment templates, comment cadence, anti-shadowban rules. Distilled from 30+ Product Hunt #1 daily launches across 150+ AI startups. **Supports 3 product paths: developer/maker (PH+GitHub), B2C consumer (Reddit/communities/TikTok, skip PH), B2B (LinkedIn+media).** 🇨🇳 产品发布与 Product Hunt 夺冠手册 — 多渠道发布的时序与节奏。T-14 预热 → T-0 发布日 → T+7 后续。Hunter 选择、maker comment 模板、评论节奏、防 shadowban。提炼自 30+ 次 Product Hunt 日冠、150+ AI 创业公司实战。**支持三种产品路径：开发者/maker（PH+GitHub）、2C 消费者（社区种子/TikTok，跳过 PH）、B2B（LinkedIn+媒体）。** 🇯🇵 プロダクトローンチ＆Product Hunt 1位プレイブック — マルチチャネルのローンチ時系列。T-14準備→T-0当日→T+7モメンタム。ハンター選定、メーカーコメント、コメントリズム、シャドウバン回避。**3つの製品パス対応：開発者/maker（PH+GitHub）、2C消費者（コミュニティ種・TikTok、PHスキップ）、B2B（LinkedIn+メディア）。** 🇰🇷 제품 출시 & Product Hunt 1위 플레이북 — 멀티채널 출시 타이밍과 시퀀싱. T-14 워밍업 → T-0 출시일 → T+7 모멘텀. 헌터 선정, 메이커 코멘트, 댓글 리듬, 섀도밴 방지. **3가지 제품 경로 지원: 개발자/maker(PH+GitHub), 2C 소비자(커뮤니티 씨드/TikTok, PH 건너뜀), B2B(LinkedIn+미디어).** Triggers: "product launch" | "launch strategy" | "Product Hunt" | "PH launch" | "how to launch" | "go to market" | "GTM" | "launch day" | "find a hunter" | "maker comment" | "launch sequencing" | "发布策略" | "产品发布" | "发 PH" | "Product Hunt 准备" | "找 hunter" | "ローンチ" | "출시 전략"
Design a consumer-driven contract testing setup — Pact configuration and CI integration. Use when asked to "set up contract testing", "configure Pact", or "add consumer-driven contracts".
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。
Foundations of individual economic decision-making, market structures, and strategic interaction. Covers supply and demand analysis, price elasticity, consumer and producer surplus, market structures (perfect competition, monopoly, oligopoly, monopolistic competition), game theory (Nash equilibrium, dominant strategies, repeated games), and welfare economics. Use when analyzing individual markets, firm behavior, pricing strategies, consumer choice, or strategic interactions between economic agents.
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。
Rebuild, re-pin, and republish Pulp's downstream demo/example repos against a new or the latest SDK. Routes natural-language requests — "update the demos to the latest SDK", "rebuild the examples against the new SDK", "check the demos still build on the new SDK", "bump every consumer's SDK pin", "open the SDK-update PRs", "republish the demo packages" — to the `pulp minos` Managed SDK Consumer Sweep: `sweep` (build + measure min-OS floors), `update` (bump each repo's SDK pin, open PRs), and `publish-runbook` (per-repo rebuild/package/publish steps).
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 managing Connected Apps for integration purposes — configuring OAuth policies, IP restrictions, refresh token expiry, pre-authorization assignment via profile or permission set, and monitoring connected app usage via EventLogFile. Also covers the running-integration operations: revoking a grant, rotating the consumer key or secret, pairing the app to an integration user's permission set, and the periodic review. Trigger keywords: 'revoke OAuth token', 'DeleteToken', 'OauthToken query returns nothing', 'ipRelaxation ENFORCE', 'permissionSetName', 'PermissionSetAssignment ExpirationDate', 'LoginHistory Application', 'connected app quarterly review', 'rotate consumer secret'. NOT for choosing which OAuth grant flow to implement — use integration/oauth-flows-and-connected-apps. NOT for decoding a specific OAuth error such as invalid_grant — use admin/connected-app-troubleshooting. NOT for authoring the full connectedApp / External Client App / Named Credential file or choosing the auth artefact — use admin/connected-apps-and-auth.
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 designing, reviewing, or troubleshooting Salesforce connected apps, External Client Apps, Named Credentials, External Credentials, and OAuth-based integration access. Triggers: 'connected app', 'OAuth flow', 'client credentials', 'JWT bearer', 'Named Credential', 'External Credential', 'integration user', 'IP restrictions', 'connectedApp-meta.xml', 'ExternalClientApplication', 'ExtlClntAppOauthSettings', 'isAdminApproved', 'refreshTokenPolicy', 'ipRelaxation', 'consumer key', 'consumer secret', 'permittedUsersPolicyType'. NOT for OAuth error codes you are already seeing — use admin/connected-app-troubleshooting. NOT for External Credential principal-type setup steps — use integration/named-credentials-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。
Use this skill to determine whether a Salesforce Commerce project should use B2B Commerce (account-gated, BuyerGroup-based, contract pricing) or D2C Commerce (consumer storefront, guest checkout, individual-based). Trigger keywords: B2B vs B2C, commerce platform selection, buyer journey, account-based purchasing, consumer storefront, licensing decision. NOT for implementation mechanics — use admin/b2b-commerce-store-setup or admin/b2c-commerce-store-setup for configuration work. NOT for Salesforce B2C Commerce (SFCC/Business Manager) 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。
Analyze consumer modeling systems for purchase prediction, lifetime value estimation, multi-touch attribution, brand affinity, and switching cost analysis. Triggers: 'evaluate CLV model', 'review purchase prediction', 'audit attribution model', 'assess customer lifetime value'.
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 consumer ordering experiences — discovery, cart, checkout, tracking, and reorder flows that convert.
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 building data pipelines, ETL jobs, event processors, message-broker producers/consumers, application caching layers, database migrations, BigQuery queries, or event-sourcing handlers in TypeScript. Triggers on edits to indexer/ETL/migration code, Prisma or Drizzle schemas, BigQuery integration code, RabbitMQ/Kafka/SQS/BullMQ producer or consumer code, Redis cache wrappers, or mentions of "data engineering", "ETL", "pipeline", "indexer", "event sourcing", "data warehouse", "data migration", "message queue", "RabbitMQ", "Kafka", "SQS", "BullMQ", "Redis cache", or "caching".
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。
Drafts legally compliant data breach notification letters to affected consumers under multi-state and federal statutes (HIPAA, GLBA, state AG requirements). Use when drafting breach notices, security incident consumer notifications, or data compromise letters.
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 and review durable REST, GraphQL, RPC, or event-facing API contracts. Use for public or shared API contracts, endpoint/schema consistency, compatibility, pagination, error semantics, and API documentation. Discovers existing consumers and conventions before recommending a style.
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。
Dev-only check that a drafted spec for THIS baseline repo won't ship dev-tree references to consumer installs. Catches three failure modes — shipped SKILL.md prose that references paths under `src/`, `tests/`, `scripts/`, `obj/` as runtime invocations (in ```bash fences``` OR `inline backticks`, plus shipped `.mjs`/`.js`/`.sh`/`.py` helper-file imports); new Python helpers added under `.claude/skills/<slug>/` (shipped helpers must be `.sh` or `.mjs`/`.js` going forward); and imports of modules that aren't in `obj/template/.claude/manifest.json` (consumer won't have the file). The aggregate scanner (`scan-shipped-skills.mjs`) walks only baseline-owned skill dirs (via `owner: baseline` frontmatter) at top level — `references/` and other subdirs are documentation, not runtime. BLOCKER findings hard-block implementation entry; ADVISORY surfaces but doesn't block. Read-only — surfaces a punch list; maintainer edits the spec and re-runs until CLEAN.
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。
Derive an execution roadmap from a project's vision/spec docs by first principles, then diff that fresh derivation against the existing roadmap to prove the task ORDER is correct. Use this whenever the user wants to review, validate, re-derive, or sanity-check an execution roadmap or delivery plan; asks whether the tasks/epics are "in the right order"; suspects a task is scheduled before its prerequisite (a producer-after-consumer / dependency-inversion error like "OpenAPI after the web client that consumes it", OR a cross-cutting inherited default like observability/auth/tenancy scheduled after the feature work that inherits it — a seam-after-consumer error); wants to find missing tasks, circular dependencies, or over-fragmented epics; or wants to compact a plan to raise velocity. Also trigger on "review the roadmap", "re-derive the plan from the spec", "is this the right build order", "check the dependency graph of our epics", "which task should come first". It reads the vision + spec corpus, decomposes actors → use-cases → modules → epics → typed tasks, identifies cross-cutting inherited-default seams, builds a real dependency graph with hard + soft (seam) edges (deterministic helper), breaks cycles, topologically orders, compacts, and emits a derived roadmap PLUS a delta report against the current one — it never blindly overwrites a hand-crafted roadmap.
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, implement, and integrate generalized validation harnesses across a producer-consumer boundary after a local harness contract exists. Use when refactoring custom validation CLIs/MCPs for large polyrepos, extending Steward across sibling repos, or deploying a local tool to a consumer project for dogfooding and testing; use mcp-harness-repo-maintainer first for initial steward.yaml adoption and cold-start proof.
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。
Implements Riverpod (v3.3.x) compile-safe state management for Flutter apps. Use when implementing @riverpod code generation providers, handling AsyncValue loading/error/data states, using ref.watch/ref.read/ref.listen, setting up ProviderScope, writing Notifier/AsyncNotifier classes, using FutureProvider/StreamProvider, applying autoDispose and family modifiers, combining providers, testing providers in isolation, scoping rebuilds with Consumer instead of ConsumerWidget, using ref.watch with select() for field-level precision, migrating from StateNotifierProvider or Riverpod 2.x patterns, handling Notifier resource lifecycle with ref.onDispose, or using experimental Mutation and offline persistence 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。
Provider (v6.x) state management for Flutter using ChangeNotifier and InheritedWidget with MVVM architecture pattern. Use this skill when implementing Provider-based state management, using Consumer/Consumer2 widgets for targeted rebuilds, accessing state with context.read/context.watch/context.select, setting up ChangeNotifierProvider or StateNotifierProvider, configuring MultiProvider for multiple providers, implementing ProxyProvider for dependent state, using Selector for optimized rebuilds, migrating from StatefulWidget to reactive state, maintaining legacy Provider codebases, debugging provider not found errors, preventing memory leaks with proper ChangeNotifier disposal, fixing context access issues in initState, or resolving .value constructor anti-patterns. Essential for apps with shared state across widgets (shopping carts, authentication, global settings, form state, theme management), when teaching state management fundamentals, or when debugging memory leaks and resource cleanup in Provider-based applications.
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。
Post-training 4-bit quantization for LLMs with minimal accuracy loss. Use for deploying large models (70B, 405B) on consumer GPUs, when you need 4× memory reduction with <2% perplexity degradation, or for faster inference (3-4× speedup) vs FP16. Integrates with transformers and PEFT for QLoRA fine-tuning.
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。
Pick a product archetype from a curated catalog before any UI gets built — the single biggest lever for not looking vibecoded. Routes the request to one of B2B-productivity, enterprise-trust, premium-consumer, playful-consumer, editorial, brutalist-distinctive, dev-tool, or marketing-landing, and returns a complete design philosophy: typography pair, color logic, motion curve, density, icon stance, reference sites, and a "feels like X" claim. Load when the user asks to pick an aesthetic, choose a design direction, decide what a UI should feel like, classify a product visually, says "what should this look like", "make this feel like [Linear/Stripe/Apple/Duolingo/...]", "give me a design direction", "what's the right aesthetic for this", or when frontend-design routes here during archetype selection. Sub-skill of frontend-design.
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。