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Modern utility-first CSS with CSS-native configuration and container queries. \n \n CSS-first configuration using @theme directives instead of JavaScript, powered by the Oxide engine for 10x faster compilation \n Native container queries ( @container , @sm: , @md: ) for component-level responsive design independent of viewport \n Comprehensive design token architecture using CSS variables for colors, spacing, typography, and semantic naming \n Mobile-first responsive breakpoints ( sm: , md: , lg

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Expert guidance for designing Zapier and Make automations that scale without complexity. \n \n Distinguishes when workflows belong in Zapier (simple, fast, maximum integrations) versus Make (complex branching, data transformation, budget optimization) \n Covers three core patterns: basic trigger-action, multi-step sequential chains, and conditional branching with different actions based on conditions \n Identifies critical anti-patterns including typing in dropdown fields, missing error handling

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 for flexible, reusable UI architecture \n Includes custom hooks for state management, async data fetching, debouncing, and context-based state with reducers \n Performance optimization techniques: memoization, code splitting with lazy loading, and list virtualization for large datasets \n Form handling

Delegate specialized tasks to isolated AI assistants with custom tools, models, and system prompts. \n \n Sub-agents preserve main context by isolating verbose tool outputs and intermediate reasoning, enabling longer sessions and cleaner conversations \n Three built-in agents available: Explore (Haiku, read-only codebase search), Plan (Sonnet, plan-mode research), and General-Purpose (Sonnet, full read/write access) \n Create custom agents in .claude/agents/ with YAML frontmatter and markdown pr

Event-Driven Architecture patterns for Spring Boot using domain events, transactional listeners, and Kafka messaging. \n \n Covers domain event design, ApplicationEventPublisher integration, and @TransactionalEventListener configuration for local event handling with AFTER_COMMIT phase guarantees \n Supports distributed messaging via Kafka and Spring Cloud Stream for inter-service communication with functional consumer beans \n Implements the transactional outbox pattern for reliable event publis

Complete Retrieval-Augmented Generation systems with LangChain4j for knowledge-enhanced AI applications. \n \n Document ingestion pipelines with configurable chunking, metadata management, and embedding generation using OpenAI or custom embedding models \n Vector search and content retrieval with filtering, re-ranking, and configurable similarity thresholds for precise context matching \n RAG-enabled AI services that automatically inject retrieved context into chat models, with support for multi

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