What problem does it solve?
It identifies and prioritizes technical debt so you can focus effort on the highest-impact remediation instead of relying on ad-hoc reviews.
Core Features & Use Cases
It scans a project for common debt signals like TODO/FIXME patterns, duplicated code, overly complex or long files, outdated or vulnerable dependencies, missing/weak typing, and low test coverage, then classifies each finding by category (Securite, Performance, Maintenabilite, Obsolescence) and scores it by impact and effort to produce a prioritization-ready report. It fits workflows where teams need periodic quality audits, pre-sprint risk reduction before major changes, or a structured input for deeper refactoring and dependency-focused analysis.
Quick Start
Ask the AI to run the tech-debt-tracker in Mode A with --scan and generate a markdown report that includes the matrix of impact versus effort and a remediation plan compatible with /refactor-planner.