patterns▌

Similarity Search Patterns \n Patterns for implementing efficient similarity search in production systems. \n Use this skill when \n \n Building semantic search systems \n Implementing RAG retrieval \n Creating recommendation engines \n Optimizing search latency \n Scaling to millions of vectors \n Combining semantic and keyword search \n \n Do not use this skill when \n \n The task is unrelated to similarity search patterns \n You need a different domain or tool outside this scope \n \n Instruc

Feature-aligned CRUD services for Spring Boot 3 with layered architecture and Spring Data JPA. \n \n Establishes feature packages with domain, application, presentation, and infrastructure layers to maintain architectural boundaries and DDD principles. \n Covers complete CRUD workflows: entity modeling with invariants, repository interfaces, JPA adapters, transactional services, DTO records, and REST controllers with proper HTTP status codes. \n Includes validation patterns using jakarta.validat

Build MCP servers with Spring AI using declarative tools, prompt templates, and native Spring integration patterns. \n \n Exposes Spring components as AI-callable tools via @Tool annotation, with parameter documentation through @ToolParam for AI model understanding \n Supports three transport modes (stdio, HTTP, SSE) with built-in Spring Security integration for role-based access control and audit logging \n Includes reusable prompt templates using @PromptTemplate , dynamic tool registration, mu

Principle-based design patterns for website sections that avoid AI-generated aesthetics. \n \n Covers five core section types: heroes, cards, CTAs, trust signals, and testimonials with context-specific guidance for different business types \n Teaches WHY and WHEN to use each pattern, not just templates; includes explicit anti-patterns like democratic design, perfect symmetry, and generic copy \n Provides cross-cutting principles on hierarchy, asymmetry, and restraint that apply across all patter

Idiomatic PyTorch patterns and best practices for building robust, efficient, and reproducible deep learning applications.

Design patterns for building autonomous coding agents with tool integration, permissions, and human oversight. \n \n Core agent loop architecture with think-decide-act-observe cycle; supports multi-model selection for different task types \n Tool design patterns including file operations, code understanding, terminal execution, and browser automation with schema-based definitions \n Permission system with four levels (auto, ask-once, ask-each, never) and risk assessment for approval workflows \n

Modern React patterns and best practices for production applications. \n \n Covers component design principles, hook extraction patterns, and state management selection across complexity levels from simple useState to global stores like Zustand and Redux Toolkit \n Includes React 19 patterns with new hooks (useActionState, useOptimistic, use) and compiler benefits for automatic memoization \n Provides composition patterns including compound components, render props vs hooks trade-offs, and highe

Core React patterns for component design, state management, and optimization.

Production-ready integration patterns for Mapbox GL JS across React, Vue, Svelte, Angular, and vanilla JavaScript. \n \n Covers framework-specific lifecycle management (useEffect/useRef in React, mounted/unmounted in Vue, onMount/onDestroy in Svelte, ngOnInit/ngOnDestroy in Angular) with proper cleanup to prevent memory leaks \n Includes Web Components pattern for framework-agnostic reusable map elements and cross-framework compatibility \n Provides token management via environment variables, Se

React and Next.js patterns for component composition, state management, performance, and accessibility. \n \n Covers component patterns including composition, compound components, and render props, plus custom hooks for state, data fetching, and debouncing \n Includes performance optimization techniques: memoization, code splitting with lazy loading, and list virtualization for large datasets \n Provides form handling with validation, error boundaries, and animation patterns using Framer Motion