desloppify

To identify technical debt across a multi-language codebase, you can scan the repository to detect code smells, dead code, and coupling problems. The tool applies static analysis heuristics to generate a standardized health report and a prioritized cleanup plan.

A codebase health score quantifies overall code quality by evaluating issues like god classes, duplicate functions, and import cycles. It helps prioritize refactoring by providing actionable recommendations to guide debt reduction efforts effectively.

Yes, you can assess code quality and generate cleanup plans for repositories with multiple architectures. The tool evaluates multi-language codebases using static analysis data to identify large files and naming issues, producing actionable cleanup guidance.

The best way to track and plan cleanups for code quality issues is to run an automated scan that generates a prioritized cleanup plan. This assesses coupling problems and dead code to guide your refactoring priorities systematically.

You detect import cycles and large files by running an automated codebase health assessment. The diagnostic process leverages static analysis heuristics to identify these structural issues and reports them within a standardized health report.