Professional Codebase Auditing

The Tech Debt Scanner is a diagnostic tool designed for developers and engineering leads who need to quantify and prioritize code quality issues. It moves beyond simple linting by analyzing codebases across five critical dimensions: comment debt, structural complexity, dependency health, test coverage gaps, and documentation staleness.

What it does

This skill performs a comprehensive, read-only analysis of your repository using standard Unix utilities. It identifies "code smells" and hidden maintenance burdens, such as deeply nested logic, oversized functions, abandoned TODOs, and outdated dependencies. Unlike manual reviews, it provides an objective inventory of issues categorized by severity.

• Structural Analysis: Detects high cyclomatic complexity and maintenance bottlenecks.
• Audit Trails: Tracks HACK/FIXME markers and orphaned documentation.
• Health Metrics: Assesses test-to-source ratios and stale lockfiles.
• Actionable Reporting: Generates a prioritized Markdown report with specific remediation steps.

Why use this skill

While an AI can "look at code," it often struggles to provide a holistic view of technical debt across thousands of files. This skill automates the discovery process, providing a structured data set that you can use for sprint planning, release readiness checks, or onboarding audits. It produces a clear severity-based hierarchy (Critical to Low), making it easy to argue for refactoring time with stakeholders.