inspektera

Auditing codebase health requires identifying architecture drift, pattern inconsistencies, and complexity hotspots with evidence-based findings. A multi-dimensional audit assigns confidence scores to each issue and tracks trajectory trends over time to monitor quality across codebases of varying sizes and languages.

Trajectory tracking for codebase quality monitoring works by appending structured updates to a HEALTH.md file after each audit. This historical record tracks health trends across multiple assessments, allowing teams to monitor whether architecture drift and complexity hotspots are improving or worsening over time.

Yes, you can run a codebase pattern audit on projects of varying sizes and languages. The assessment enforces structured artifact formats and plan-relative staleness checks, making it applicable across diverse codebases to identify test gaps and dependency health issues without specific framework restrictions.

The best way to document codebase health findings is to append evidence-based results to a HEALTH.md file while simultaneously feeding actionable items into a TODO.md file. This structured workflow ensures quality gaps, architecture drift, and staleness issues are tracked for follow-on planning.

Codebase audit reports include confidence scores and plan-relative staleness checks to enforce evidence-based findings and ensure artifact-writing rules are aligned with the workflow. This structured approach prevents false positives and highlights outdated documentation relative to your current architectural plan.