Skill UI

This skill provides a comprehensive framework for conducting high-quality code reviews. It guides developers through checking code across four critical dimensions: Correctness (functional accuracy and edge cases), Maintainability (readability and documentation), Performance (efficiency and resource usage), and Security (input validation and vulnerability management). It also emphasizes providing actionable, constructive, and empathetic feedback.

Provides a comprehensive, layered reference architecture for building production-grade integrations with Webflow's Data API v2. This guide separates concerns into distinct layers: API access, business logic (CMS, e-commerce), webhook handling, and caching, ensuring scalability and maintainability for complex web applications.

This guide outlines a systematic workflow to eliminate copy-paste duplication (code clones) detected by tools like jscpd. It teaches developers how to refactor repeated code into shared functions, modules, constants, or base classes. Use this process when your codebase exhibits significant redundancy to improve maintainability, reduce technical debt, and enhance overall code quality.

This skill provides a comprehensive tech debt assessment, identifying, classifying, and prioritizing core maintainability issues. By drawing on classic engineering principles, it helps teams build a structured refactoring roadmap, optimizing code health and development velocity.

This skill provides comprehensive pull request (PR) code reviews that go beyond simple syntax checks. It aggressively surfaces deep-rooted decay risks, architectural design smells, and maintainability issues. Findings are reported using a structured Symptom → Source → Consequence → Remedy framework, drawing insights from classic engineering principles. Ideal for reviewing complex or crucial code modules.

This skill helps developers structure and record critical architectural decisions (ADRs) made during coding sessions. It automatically detects moments of decision, capturing the context, alternatives considered, and the rationale (trade-offs and consequences). This maintains a living log that explains 'why' the code base was built the way it is, preventing knowledge loss and improving project maintainability.

Code Health MCP provides structural maintainability feedback and design-level health scores, going beyond standard linting. It is crucial for AI-assisted coding workflows, allowing users to review code quality, verify score deltas after changes, and gate commits or pull requests to prevent codebase regression. Use it when refactoring, updating legacy modules, or ensuring the integrity of large diffs.

This comprehensive guide establishes foundational coding standards and best practices for enhancing code quality, readability, and maintainability across all projects. It covers naming conventions, immutability patterns, error handling, and core design principles like KISS, DRY, and YAGNI, applicable to TypeScript, JavaScript, and React development. Use it when starting a new module or performing code reviews.

This guide details the Hexagonal Architecture (Ports and Adapters) pattern, a robust method for decoupling core business logic from external infrastructure concerns. It teaches how to structure applications to make the domain model independent of databases, UI frameworks, or message queues. Implementing this pattern drastically improves testability, maintainability, and the ability to swap out external services without rewriting business rules.

A structured workflow designed to prevent 'reinventing the wheel.' Before writing custom code, this skill guides the user through analyzing needs, conducting parallel searches across multiple channels (npm, PyPI, GitHub, MCP), evaluating candidate solutions based on maintainability and community support, and making a decision (Adopt, Extend, or Custom Build). It ensures that solutions leverage existing, proven libraries and patterns.

A comprehensive assistant designed to analyze existing codebases for adherence to SOLID principles, common code smells, and complexity metrics. It identifies anti-patterns like tight coupling, excessive responsibility, and duplication, providing prioritized, actionable refactoring suggestions to improve code maintainability and quality.

This tool automatically formats Python code using the industry-standard 'black' formatter. It ensures your codebase adheres to consistent style guidelines, improving readability and maintainability across the entire team. Ideal for development workflows and code reviews.