Skill UI

This comprehensive tool performs an architectural audit of a codebase, mapping module dependencies, checking layering integrity, and flagging structural decay. Drawing on classic engineering principles (like Conway's Law and Testability Seams), it provides a deep assessment of the project's health and structure. Ideal for large-scale code reviews or onboarding new developers.

This library provides comprehensive patterns for building robust Clinical Decision Support Systems (CDSS) integrated into Electronic Medical Records (EMR). It ensures patient safety by implementing critical checks such as drug interaction screening, weight/age/renal-adjusted dose validation, and standardized clinical scoring (e.g., NEWS2). The engine uses pure functions, guaranteeing high testability and reliability for critical medical insights.

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.

This skill performs a comprehensive architecture audit on codebases by mapping module dependencies and checking layering integrity. It identifies structural decay using principles from classic engineering books. The tool generates Mermaid dependency graphs, assesses testability seams, and applies Conway's Law checks to ensure architectural health. It is suitable for developers needing to understand codebase structure, review folder organization, or detect circular imports before refactoring.

A comprehensive guide and shared vocabulary for designing and structuring complex software modules. Use this when you need to refine an existing module's interface, identify opportunities for deepening its capabilities, determine optimal internal seams, or improve code testability and AI-navigability. It establishes clear principles for Module, Interface, Depth, and Seam.

This skill acts as an expert AI-powered code review specialist combining automated static analysis and intelligent pattern recognition. It leverages tools like GitHub Copilot, SonarQube, and CodeQL to identify bugs, vulnerabilities, and performance issues across 30+ languages. It supports CI/CD integration, security vulnerability analysis, architectural coherence checks, and actionable recommendations for maintainability and testability within modern DevOps workflows.