code-analysis

Analyze codebase architecture, metrics, and tech debt for review.

12|2|Updated Nov 20, 2025

Search Tags:#code quality #architecture #code analysis #refactoring #metrics #tech debt

Ready to run

npx skills add https://github.com/alexandrbasis/wythm-claude-workflows --skill code-analysis-alexandrbasis

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: code-analysis
Source: https://github.com/alexandrbasis/wythm-claude-workflows/tree/main/.claude/skills/code-analysis
Command: npx skills add https://github.com/alexandrbasis/wythm-claude-workflows --skill code-analysis-alexandrbasis

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill provides a comprehensive analysis of codebases, identifying architectural issues, code quality metrics, and technical debt to improve software quality and maintainability.

Core Features & Use Cases

Architecture Review: Analyzes layers, boundaries, and dependencies.
Code Quality Metrics: Assesses complexity, test coverage, and duplication.
Tech Debt Assessment: Identifies TODOs, deprecated patterns, and missing error handling.
Use Case: Use this skill during a code review to get a detailed report on potential architectural violations and areas needing refactoring.

Quick Start

Use the code-analysis skill to perform a deep code analysis of the current project.

Frequently Asked Questions about code-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I assess tech debt and code quality metrics in my project?▼

To assess tech debt and code quality metrics, you analyze project structure, module dependencies, and identify deprecated patterns or missing error handling. This process reveals TODOs, architectural violations, and areas needing refactoring.

What is the best way to verify DDD layer separation and NestJS module boundaries?▼

Verifying DDD layer separation and NestJS module boundaries involves analyzing service injection patterns and module dependencies. This architectural review ensures layers remain distinct and checks for dependency violations across your codebase.

How do I perform an architecture review using codebase exploration?▼

Performing an architecture review through codebase exploration requires analyzing layers, boundaries, and dependencies alongside git history insights. This generates a detailed report highlighting potential structural violations and architectural issues.

Does this code analysis approach work with Prisma schema consistency checks?▼

Yes, code analysis supports Prisma schema consistency checks. It evaluates schema structures against your codebase to ensure data layer alignment, while verifying domain exceptions and error handling patterns.

Can I identify missing error handling and domain exceptions during a code review?▼

Yes, you can identify missing error handling and domain exceptions during a code review. The analysis specifically targets these tech debt items, verifying that error handling correctly implements domain-specific exception patterns.

When should I use automated code analysis for refactoring recommendations?▼

Use automated code analysis for refactoring recommendations when you need deep insights into code quality metrics, complexity, and duplication. It provides actionable recommendations for improving software maintainability during code reviews.