Skill UI

Expert in designing and implementing advanced Retrieval-Augmented Generation (RAG) pipelines. This role focuses on optimizing the entire information retrieval process—from document chunking and embedding model selection to vector database architectures and hybrid search strategies. The goal is to bridge the gap between raw knowledge documents and accurate LLM understanding, drastically reducing hallucination and enhancing context relevance for enterprise applications.

This comprehensive workflow guides the end-to-end implementation of Retrieval-Augmented Generation (RAG) systems. It covers critical stages, including selecting optimal embedding models, setting up vector databases, designing chunking strategies, implementing hybrid retrieval, integrating Large Language Models (LLMs), and performing rigorous evaluation. Use this when building knowledge-grounded AI applications or advanced semantic search systems.

Specializes in building modern, high-performance Rails 7+ web applications. Expertise includes optimizing Active Record queries (N+1 prevention), implementing partial page updates with Hotwire (Turbo Frames/Streams), handling real-time communication via Action Cable, and managing background jobs using Sidekiq. The process includes rigorous RSpec testing and database schema management.

A comprehensive optimization guide maintained by Vercel, covering 45 rules for React and Next.js. Use this resource when building new components, implementing complex data fetching (client or server-side), refactoring code, or systematically improving bundle size and overall load times for high-performance web applications.

Automated assistance for building React components, offering best practices, production-ready code generation, and validation guidance for frontend patterns like accessibility and performance optimization.

A senior specialist for building modern, production-grade React applications using React 19, Server Components, and Next.js App Router. Expertise includes implementing complex state management (Redux, Zustand), optimizing performance with memoization, handling data fetching with TanStack Query, and ensuring strict TypeScript typing and accessibility standards. Ideal for architecting large-scale frontend systems.

A comprehensive architectural guide for building production-grade flowcharts using ReactFlow. This pattern set covers key challenges including hierarchical tree navigation (expandable/collapsible nodes), performance optimization via incremental rendering and memoization, and advanced state management using Redux-like reducer patterns with history tracking (undo/redo).

This skill guides developers through modernizing React applications. It covers migrating from class components to functional components using hooks, upgrading React versions, adopting concurrent features (like Suspense), and applying automated refactoring techniques using codemods. It is essential for maintaining high-performance, modern React codebases and integrating TypeScript.

Builds and optimizes production-ready React Native and Expo mobile apps, covering navigation hierarchies, native module setup, FlatList performance tuning, SafeArea/keyboard handling, and multi-platform testing to ensure smooth iOS and Android releases.

A comprehensive guide to modern React state management patterns. It covers various state types—including local, global, server, and form state—and demonstrates best practices using industry-leading libraries like Redux Toolkit, Zustand, Jotai, and React Query. Use this when building complex, scalable React applications and needing to select the optimal state solution.

A practical decision framework for determining whether to use regular expressions or Large Language Models (LLMs) when parsing structured text (e.g., forms, quizzes, invoices). It recommends starting with deterministic, low-cost regex for 95-98% of structured data, and only invoking expensive LLM calls for identifying and validating ambiguous edge cases, optimizing both cost and accuracy.

Automate Render cloud platform operations—listing services/projects, triggering and monitoring deployments—using Composio's Render toolkit through the Rube MCP integration, keeping schemas current via RUBE_SEARCH_TOOLS.