Skill UI

This optimizer guides the acceleration of complex, multi-stage processes, such as CI/CD pipelines, large-scale refactoring, or data validation. It instructs users to decompose large tasks into independent execution lanes, build a dependency graph, batch read/check operations, and manage writes with strict isolation to maximize speed without sacrificing correctness. Ideal for optimizing development workflows and testing cycles.

A comprehensive guide to Test-Driven Development (TDD) for Quarkus 3.x LTS, focusing on event-oriented architectures. This framework utilizes JUnit 5, Mockito, REST Assured, Apache Camel, and JaCoCo to ensure high code coverage (80%+). Use it when developing new features, fixing bugs, or refactoring event-driven services and API endpoints.

A comprehensive guide detailing advanced performance optimization patterns for React 18/19 and Next.js. Adapted from Vercel Engineering's best practices, this skill organizes 70+ critical rules across eight categories—including eliminating waterfalls, optimizing bundle size, improving server-side rendering, and managing client-side re-renders. Use this when developing, reviewing, or refactoring high-performance React applications.

repo-scan is a powerful tool designed to audit large, complex, cross-stack codebases (C++, Java, iOS, Web). It classifies every file into project code, third-party dependencies, or build artifacts. Key features include detecting embedded libraries (e.g., FFmpeg, OpenSSL) and providing a practical 4-stage assessment (Core Asset / Extract / Refactor / Deprecate) via an interactive HTML report. Essential for managing monorepos and planning major refactoring efforts.

This skill provides deep insights into idiomatic Rust development. It covers core concepts like ownership and borrowing to prevent data races, robust error handling using `anyhow` and `thiserror`, advanced pattern matching with enums, and utilizing traits and generics for safe abstraction. Master these patterns when writing or refactoring complex, high-performance, and reliable Rust applications.

This tool initializes a structured multi-agent swarm with built-in anti-drift configuration. It is designed for orchestrating complex, multi-file tasks that require coordinated efforts from three or more specialized AI agents, such as feature implementation, cross-module refactoring, or comprehensive security audits. It supports various topologies (hierarchical, mesh, etc.) to ensure robust and manageable parallel work execution across large teams.

This comprehensive guide outlines an opinionated set of conventions for building robust Ruby on Rails applications. It covers core architectural principles, including rich models, state-as-records, minimal dependencies, and best practices for CRUD operations and testing. It is mandatory to consult these guidelines whenever designing, writing, reviewing, or refactoring any Rails code.