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Found 387 Skills
Next.js 15 App Router patterns. Trigger: When working in Next.js App Router (app/), Server Components vs Client Components, Server Actions, Route Handlers, caching/revalidation, and streaming/Suspense.
Master context engineering for AI agent systems. Use when designing agent architectures, debugging context failures, optimizing token usage, implementing memory systems, building multi-agent coordination, evaluating agent performance, or developing LLM-powered pipelines. Covers context fundamentals, degradation patterns, optimization techniques (compaction, masking, caching), compression strategies, memory architectures, multi-agent patterns, LLM-as-Judge evaluation, tool design, and project development.
System architecture skill for designing scalable, maintainable software systems. Covers microservices/monolith decisions, API design, DB selection, caching, security, and scalability planning.
This skill provides comprehensive knowledge for TanStack Query v5 (React Query) server state management in React applications. It should be used when setting up data fetching with useQuery, implementing mutations with useMutation, configuring QueryClient, managing caching strategies, migrating from v4 to v5, implementing optimistic updates, using infinite queries, or encountering query/mutation errors. Use when: initializing TanStack Query in React projects, configuring QueryClient settings, creating custom query hooks, implementing mutations with error handling, setting up optimistic updates, using useInfiniteQuery for pagination, migrating from React Query v4 to v5, debugging stale data issues, fixing caching problems, resolving v5 breaking changes, implementing suspense queries, or setting up query devtools. Keywords: TanStack Query, React Query, useQuery, useMutation, useInfiniteQuery, useSuspenseQuery, QueryClient, QueryClientProvider, data fetching, server state, caching, staleTime, gcTime, query invalidation, prefetching, optimistic updates, mutations, query keys, query functions, error boundaries, suspense, React Query DevTools, v5 migration, v4 to v5, request waterfalls, background refetching, cacheTime renamed, loading status renamed, pending status, initialPageParam required, keepPreviousData removed, placeholderData, query callbacks removed, onSuccess removed, onError removed, object syntax required
Instruction set for enabling and operating the Spring Cache abstraction in Spring Boot when implementing application-level caching for performance-sensitive workloads.
Use when serving uploaded files to users. Covers API-proxied file serving, direct storage URLs (S3/R2/Cloudinary), CDN configuration, public file URLs, caching headers, image optimization with Cloudinary, and serving files in frontend applications.
Patterns for SQLite databases in Python projects - state management, caching, and async operations. Triggers on: sqlite, sqlite3, aiosqlite, local database, database schema, migration, wal mode.
Plan and build production-ready FastAPI endpoints with async SQLAlchemy, Pydantic v2 models, dependency injection for auth, and pytest tests. Uses interview-driven planning to clarify data models, authentication method, pagination strategy, and caching before writing any code.
Next.js App Router development with TypeScript. Server Components, Server Actions, caching, MUI. Use when creating pages, components, fetching data, or building features.
Guides the usage of Gemini API on Google Cloud Vertex AI with the Gen AI SDK. Use when the user asks about using Gemini in an enterprise environment or explicitly mentions Vertex AI. Covers SDK usage (Python, JS/TS, Go, Java, C#), capabilities like Live API, tools, multimedia generation, caching, and batch prediction.
Builds ASP.NET Core APIs, EF Core data access, gRPC, SignalR, and backend services with middleware, security (OAuth, JWT, OWASP), resilience, messaging, OpenAPI, .NET Aspire, Semantic Kernel, HybridCache, YARP reverse proxy, output caching, Office documents (Excel, Word, PowerPoint), PDF, and architecture patterns. Spans 32 topic areas. Do not use for UI rendering patterns or CI/CD pipeline authoring.
Apply when scoping, reviewing, or documenting cross-cutting VTEX commerce architecture across storefront, IO, headless, marketplace, payments, or any other VTEX module. Grounds work in the Well-Architected Commerce framework—Technical Foundation (reliability, trust, integrity; security, infrastructure, compliance), Future-proof (innovation, simplicity, efficiency; scalable and adaptable solutions), and Operational Excellence (accuracy, accountability, data-driven improvement; process and customer experience). Routes implementation detail to product tracks (IO caching and paths, Master Data strategy, marketplace integrations). Use for solution design, architecture reviews, and RFP-level technical structure.