tech-debt-analyzer

To identify technical debt in JavaScript and TypeScript repositories, scan source files for code smells like large files, complex functions, and magic numbers, then classify findings using a standardized debt taxonomy. This process prioritizes fixes before maintainability issues slow delivery.

The best way to audit dependencies for code maintenance is to review packages for outdated, deprecated, duplicate, or risky choices. Dependency analysis identifies security vulnerabilities and stability risks, allowing teams to document findings and prioritize remediation work.

Create a prioritized debt register by analyzing the repository for technical debt, scoring findings by severity and impact across categories like architecture and security, and mapping remediation recommendations to standardized tracking templates for the next sprint.

Yes, technical debt analysis covers architecture review and documentation assessment by applying a comprehensive taxonomy. It classifies findings across code quality, architecture, testing, documentation, dependency, performance, security, infrastructure, and design categories.

Yes, you can detect code smells automatically by scanning source files for large files, complex functions, long parameter lists, deep nesting, magic numbers, and leftover debug statements. This identifies maintainability issues for refactoring planning.