Skill UI

This skill provides a systematic pipeline for safely executing large-scale code refactors across multiple files or subsystems. It first performs parallel, dependency-aware analysis to map the entire scope, synthesizing a single, actionable plan. The process then breaks the work into independent 'work packets,' which are executed sequentially or in parallel by specialized worker agents, ensuring strict dependency management and behavior parity throughout the entire process.

This skill reviews code differences (diffs) to identify opportunities for improvement in clarity, reusability, efficiency, and overall quality. It employs multiple specialized sub-agents (e.g., Code Reuse, Efficiency, Quality) to audit changes. It can provide high-confidence, behavior-preserving fixes when requested, ensuring the code adheres to best practices without introducing regressions. Best used when refactoring, cleaning up, or auditing a specific code scope.

A comprehensive guide detailing how to refactor large, complex SwiftUI views into smaller, more stable, and explicit components. It emphasizes adopting a lightweight state approach (favoring local state and environment variables over excessive view model layers) to improve data flow, readability, and overall code maintainability in modern iOS development.

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.

Guides AI agents through analyzing working code, spotting overly complex structures, then refactoring for clarity while preserving exact behavior and project conventions, especially after reviews or high-pressure edits.

A comprehensive guide detailing recommended naming conventions for various Go language elements, including packages, structs, interfaces, constants, functions, and error handling. Use this skill when writing, reviewing, or refactoring Go code to ensure adherence to idiomatic Go style.

This framework provides a rigorous, multi-dimensional guide for conducting code reviews. It evaluates five critical axes: correctness, readability, architecture, security, and performance. Use this process before merging any code change, especially when reviewing PRs, refactoring, or evaluating code produced by AI agents, to ensure continuous improvement and maintain high code health.

Behavioral guidelines for writing, reviewing, and refactoring code with LLMs, emphasizing minimalism, clear assumptions, surgical edits, and verifiable success criteria to avoid common machine-assisted coding mistakes.

This document defines the strict, mandatory structure and deterministic rules for creating implementation plans. It ensures that plans for new features, refactoring, or architectural changes are fully self-contained, machine-readable, and structured for automated execution by advanced AI agents or human teams.

This skill transforms a raw Python script into a polished, beginner-friendly project package. It automatically refactors the code to adhere to PEP 8 standards, adds comprehensive, instructional comments explaining the 'why' behind the logic, and generates a complete, professional `README.md` file. The resulting project is immediately ready for use in educational settings, portfolios, or for onboarding new developers.

Shows how to apply the Extract Method refactoring in Java to improve readability, modularity, and testability by isolating reusable behaviors from complex methods while preserving the original functionality.

This skill focuses on the 'Remove Parameter' refactoring pattern specific to Java development. It teaches systematic techniques to analyze methods and identify unused or redundant parameters. By applying this refactoring, developers can significantly improve code readability, enhance maintainability, reduce coupling, and simplify method signatures while preserving original functionality and logic.