burndown

Automate tech debt cleanup by applying phase-based detection to scan for code quality issues, prioritizing them by severity, and iteratively applying fixes. This autonomous loop reduces maintenance burden without requiring constant manual intervention across codebases of any size.

Autonomous code quality detection scans a codebase to identify code slop and architectural issues, prioritizes findings by severity, and applies iterative fixes. It uses linting and re-scans to verify debt reduction until a completion checkpoint confirms no critical issues remain.

Yes, tech debt detection and fixes can be scoped to targeted directories or files as needed. This allows you to efficiently burn down debt in specific areas without scanning the full codebase, while still meeting the strict checkpoint-driven workflow.

The checkpoint-driven workflow validates progress using a completion-checkpoint.json file and re-scan verification to ensure debt reduction. Optional browser verification can also confirm UI stability, guaranteeing no critical code quality issues remain after autonomous fixes.

The best way to eliminate code slop and architectural debt is using an autonomous detection and fix loop that scans for issues, prioritizes by severity, and applies fixes iteratively. Linting and re-scans verify reduction until completion checkpoints confirm no critical issues remain.

An autonomous fix loop reduces maintenance burden by detecting and fixing code quality issues end-to-end without constant manual intervention. Unlike manual linting, it applies phase-based detection, iterative fixes, and re-scan verification to validate debt reduction through completion checkpoints.