What problem does it solve? Technical debt accumulates silently in codebases through TODO comments, workarounds, and outdated dependencies, making it hard to track what needs fixing and when. This Skill scans for debt indicators, maintains a structured debt register, and prioritizes repayment so teams can make conscious decisions about code quality. ## Core Features & Use Cases - Automated Debt Scanning: Detects TODO, FIXME, and HACK comments, deprecated markers, duplicated code, oversized files, and overly long functions, then categorizes findings into architecture, code quality, test, documentation, dependency, and performance debt. - Debt Register Management: Adds manual entries with category and effort estimates, and maintains a persistent register at docs/tech-debt-register.md with IDs, impact ratings, and sprint assignments. - Priority Scoring and Reporting: Re-sorts the register using an impact-times-frequency-over-effort formula and generates trend reports flagging items older than three sprints. - Use Case: Before sprint planning, run a scan to catch new debt, then prioritize the register to decide which high-impact, low-effort items to schedule into the upcoming sprint. ## Quick Start Use the tech-debt skill to scan this codebase for debt indicators and write the findings to the debt register.
