Can it help with testing and documentation?

The skill specifically checks for test coverage gaps and documentation quality, ensuring your code is both reliable and well-explained.

How does the skill identify DRY violations?

The skill scans your source files for logic duplication and suggests ways to extract shared utilities, reducing maintenance overhead.

Does it support SOLID principle analysis?

Yes, it evaluates your class and function structures against Single Responsibility, Open/Closed, and other SOLID principles to ensure scalable architecture.

Are the suggested fixes easy to implement?

Every report provides a 'Suggested Fix' code block that demonstrates exactly how to refactor the problematic code, making implementation straightforward.

Code Quality & Best Practices Checker

Name: Code Quality & Best Practices Checker
Author: lexicalninja

bylexicalninja

Developer Tools

Analyzes source code to identify architectural flaws, pattern violations, and maintainability issues while providing actionable improvement suggestions.

About

The Best Practices Checker is a specialized Claude Code skill designed to act as an automated code reviewer and architectural auditor. It systematically evaluates codebases against industry-standard principles such as DRY and SOLID, while also scrutinizing error handling, test coverage, and documentation quality. By generating structured reports that include specific line references, code snippets for suggested fixes, and clear priority levels, this skill helps developers maintain high engineering standards, reduce technical debt, and accelerate the peer review process with precise, context-aware feedback.

Key Features

0 GitHub stars
Comprehensive analysis of error handling and propagation patterns
Structured reports with line-specific improvements and justifications
Priority-based labeling (Must-Fix, Should-Fix, Nice-to-Have)
Automated DRY and SOLID principle verification
Evaluation of testing quality, coverage, and documentation standards

Use Cases

Onboarding and mentoring team members by providing educational explanations for code improvements
Automated pre-PR code reviews to ensure consistency and prevent technical debt
Auditing legacy codebases to identify refactoring opportunities and architectural weaknesses

About

Key Features

0 GitHub stars
Comprehensive analysis of error handling and propagation patterns
Structured reports with line-specific improvements and justifications
Priority-based labeling (Must-Fix, Should-Fix, Nice-to-Have)
Automated DRY and SOLID principle verification
Evaluation of testing quality, coverage, and documentation standards

Use Cases

Onboarding and mentoring team members by providing educational explanations for code improvements
Automated pre-PR code reviews to ensure consistency and prevent technical debt
Auditing legacy codebases to identify refactoring opportunities and architectural weaknesses