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Testing strategies for Next.js: Server Components, Client Components, Server Actions, Route Handlers, end-to-end with Playwright. Vitest/Jest configuration, React Testing Library patterns, msw for network mocks. Use this skill to: - Pick the right test layer for what you're testing. - Configure Vitest or Jest for Next.js. - Test Server Components without running them in isolation. - Test Server Actions and Route Handlers as pure functions. - Set up Playwright for e2e and integration of RSC. Do NOT use this skill for: - General Next.js conventions (see nextjs-conventions). - RSC vs Client model (see server-component-patterns). - Plain Node.js test patterns (see nodejs-plugin equivalents).

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。

Testing React Native: Jest with jest-expo / react-native preset, React Testing Library Native, native module mocking, hook testing. Optional sections for Detox (native automation) and Maestro (declarative YAML e2e). Use this skill to: - Configure Jest preset based on workflow. - Write component tests with @testing-library/react-native. - Mock native modules (react-native-reanimated, expo-*, react-native-mmkv). - Test custom hooks via renderHook. - Set up Detox or Maestro for e2e (optional, requires native toolchain). Do NOT use this skill for: - General RN conventions (see rn-conventions). - Web-React testing (see react-plugin:react-testing — different jsdom setup). - Plain Node testing patterns (see nodejs-plugin equivalents).

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。

React Server Components vs Client Components in Next.js: the boundary discipline, "use client" / "use server" directives, Server Actions, what serializes across the boundary, common pitfalls. Use this skill to: - Decide whether a component should be RSC or Client. - Push the "use client" boundary as deep as possible. - Implement Server Actions correctly (auth, validation, revalidation). - Compose RSC and Client components without breaking the model. - Pass data across the boundary safely. Do NOT use this skill for: - General Next.js conventions (see nextjs-conventions). - Specific data-fetching APIs and caching (see nextjs-data-fetching). - Routing (see nextjs-routing).

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。

State management for Angular 18-21: signals (signal/computed/effect), services-as-state, NgRx Store + Effects + Selectors, NgRx Component Store, NgRx Signals (newer signal-based store). RxJS essentials — operators, async pipe, takeUntilDestroyed, signal/observable interop. Use this skill to: - Pick the right state tool (signals / services / NgRx variant / vue-query equivalent). - Use signals correctly (signal/computed/effect — when each). - Build a Pinia-style service-as-state singleton. - Set up NgRx Store + Effects + Selectors. - Use RxJS without leaking subscriptions (async pipe, takeUntilDestroyed, Subject patterns). - Bridge signals ↔ observables via toSignal / toObservable. Do NOT use this skill for: - General Angular conventions (see angular-conventions). - Routing state (see angular-routing). - Form state (see angular-forms). - Testing state (see angular-testing).

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。

Testing Angular 18-21: TestBed, component harnesses (@angular/cdk/testing), Karma+Jasmine (default historical) vs Jest (jest-preset-angular, modern), Angular Testing Library (RTL-style). HttpClient mocking via HttpTestingController. NgRx Effects testing. Cypress / Playwright e2e. Use this skill to: - Detect runner (Karma+Jasmine vs Jest) and configure correctly. - Write component tests with TestBed. - Use component harnesses for Material / custom UI components. - Mock HttpClient via provideHttpClientTesting + HttpTestingController. - Test signal-based inputs with componentRef.setInput(). - Test NgRx Effects with provideMockActions. Do NOT use this skill for: - General Angular conventions (see angular-conventions). - Routing patterns broadly (see angular-routing — covers testing routes briefly). - Form patterns broadly (see angular-forms).

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Search the general web or scholarly publications through Exa. Use for current public information, official documentation, source code, release notes, papers, preprints, journals, or literature research.

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Use when the user wants to elicit refused directions, generalize them, and close matching tracker items as not planned. Not for duplicates, spam, or items closed as completed or obsolete.

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 writing, editing, cleaning, or refactoring Tailwind classes, components, or configuration. Not for read-only audits of Tailwind code, or general CSS without Tailwind.

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 reconciling an API endpoint's generated OpenAPI schema and declared response types with its actual runtime response. Not for general API documentation: use docs-and-adrs.

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。

Migrate workloads from Google Cloud Platform to AWS — including AI and agentic workloads regardless of cloud provider. Triggers on: migrate from GCP, GCP to AWS, move off Google Cloud, migrate Terraform to AWS, migrate Cloud SQL to RDS, migrate GKE to EKS, migrate Cloud Run to Fargate, Google Cloud migration, migrate from OpenAI to Bedrock, move off OpenAI, switch from ChatGPT API to AWS, migrate from Gemini to Bedrock, migrate LangChain to Bedrock, migrate LangGraph to AWS, migrate agentic workloads to AWS, move AI workloads to AWS, migrate my AI app to AWS. Runs a 6-phase process: discover GCP resources from Terraform files, app code, or billing exports, clarify migration requirements, design AWS architecture, estimate costs, generate migration artifacts, and collect optional feedback. Clarify must finish before Design, Estimate, or Generate. Includes AI provider migration guidance (for example, OpenAI to Amazon Bedrock) by selecting closest-fit Bedrock model families for required modality, latency/quality targets, context windows, and cost constraints. Model mapping is compatibility-guided, not 1:1 parity; validate prompts, tool-calling behavior, and eval metrics before cutover. Do not use for: Azure or on-premises migrations to AWS, AWS-to-GCP reverse migration, general AWS architecture advice without migration intent, GCP-to-GCP refactoring, or multi-cloud deployments that do not involve migrating off GCP.

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Use only for user-provided academic text, explicit scholarly claims, existing citations, or known bibliographies needing citations added, verified, replaced, extracted, or formatted. Supports claim-to-source matching, citation-support checks, replacements, and common academic citation formats. Do not use for general fact-checking, legal/journalistic citation work, open-ended 'find literature about X', topic-level exhaustive discovery, systematic-review corpus construction, PRISMA searches, or creating new research claims. Chinese: 为已有段落补参考文献、核验已有引用、替换错误引用、提取需引文论断、GB/T 7714 格式化.

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。

Routes general Convex requests to the right project skill. Use when the user asks which Convex skill to use or gives an underspecified Convex app task.

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TypeScript and JavaScript performance and code-quality rules, usable in any framework. Use when writing, reviewing, or refactoring hot paths, data-structure choices, async flows, or bundle-size-sensitive code. Triggers include "optimize this function", "too slow", "reduce allocations", "bundle size", "lazy load", "speed up imports", or general code review of utilities and services.

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Use this skill when the user needs official desktop Obsidian CLI Bases or Bookmarks workflows, including base discovery, view/query operations, base item creation, and bookmark management. Keep this skill separate from general note CRUD, runtime admin, Sync/Publish, and devtools diagnostics.

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 operating Inngest API resources from the terminal with `npx inngest-cli@latest api`: Cloud/local run debugging, event-run lookup, function traces, function invocation, app syncs, webhooks, environments, keys, account checks, and Insights queries. Provides prescriptive command routing for agents: which CLI command to run for a run ID, event ID, app ID, function ID, Cloud environment, API key, missing ID, or potentially mutating operation. Use `inngest-cli` for dev server setup/general CLI workflows and `inngest-api` only when raw REST API v2 docs or OpenAPI fallback are needed.

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Author, review, or batch-produce SVG icon hover gestures and icon↔icon morphs (Hugeicons/Lucide/Phosphor). Use for animated icon, icon hover, per-icon gesture, icon morph, menu↔cross, stroke-dashoffset draw-on, pathLength, transform-box. Not for page transitions, Lottie, or general UI chrome motion.

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Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files). Triggers include: any mention of 'Word doc', 'word document', '.docx', or requests to produce professional documents with formatting like tables of contents, headings, page numbers, or letterheads. Also use when extracting or reorganizing content from .docx files, inserting or replacing images in documents, performing find-and-replace in Word files, working with tracked changes or comments, or converting content into a polished Word document. If the user asks for a 'report', 'memo', 'letter', 'template', or similar deliverable as a Word or .docx file, use this skill. Do NOT use for PDFs, spreadsheets, Google Docs, or general coding tasks unrelated to document generation.

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Meta-agent for creating new custom agents, skills, and MCP integrations. Expert in agent design, MCP development, skill architecture, and rapid prototyping. Activate on 'create agent', 'new skill', 'MCP server', 'custom tool', 'agent design'. NOT for using existing agents (invoke them directly), general coding (use language-specific skills), or infrastructure setup (use deployment-engineer).

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"Habitual Domain (HD) theory by Taiwanese scholar P.L. Yu (游伯龍, 1977) — integrates four domains (potential/actual/reachable/activated), eight general hypotheses, seven-layer decision structure, and nine HD-expansion tools to analyze decision blind spots, break cognitive inertia, and support cross-domain integration. Use for diagnosing why alternatives are invisible, decision paralysis, breaking cognitive frames, or explaining perception gaps between people. Triggers: 『思維框架』『打破盲點』『創新思考』『決策盲區』『跨域整合』『游伯龍』『習慣領域』『HD 理論』『七層決策』『四領域』『八大通性』『P.L. Yu』. Especially for NYCU EMBA HD course, 政大科管所, 中山企管系 decision-analysis/innovation/leadership courses. Taiwan-origin theory cited in J. Optimization Theory, Theory & Decision, Human Systems Management.".

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Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats. This skill should be used when analyzing any scientific data file to understand its structure, content, quality, and characteristics. Automatically detects file type and generates detailed markdown reports with format-specific analysis, quality metrics, and downstream analysis recommendations. Covers chemistry, bioinformatics, microscopy, spectroscopy, proteomics, metabolomics, and general scientific data formats.

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 whenever the user wants to create, read, edit, or manipulate Word documents (.docx files). Triggers include: any mention of 'Word doc', 'word document', '.docx', or requests to produce professional documents with formatting like tables of contents, headings, page numbers, or letterheads. Also use when extracting or reorganizing content from .docx files, inserting or replacing images in documents, performing find-and-replace in Word files, working with tracked changes or comments, or converting content into a polished Word document. If the user asks for a 'report', 'memo', 'letter', 'template', or similar deliverable as a Word or .docx file, use this skill. Do NOT use for PDFs, spreadsheets, Google Docs, or general coding tasks unrelated to document 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。

"Implement Generalized Second Price auction for ad slot allocation and pricing. Use this skill when the user needs to understand search ad auctions, compute ad positions and costs-per-click, or analyze bidding dynamics — even if they say 'how does Google Ads auction work', 'ad rank calculation', or 'second price auction for ads'.".

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 comprehensive unit tests with proper structure, mocking, and coverage. Use for general unit testing guidance across languages.

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Use when planning a source-grounded method overview, architecture, pipeline, system/data-flow, mechanism, or agent-workflow figure for a CS or deep-learning paper. Produces an editable figure brief before image generation or manual redrawing; not for plots, tables, or general prose.

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。