Code Health with Repowise

Repowise scores every file 1–10 from deterministic markers — McCabe complexity, deep nesting, brain methods, class cohesion (LCOM4), god classes, clone detection, untested hotspots, function-level churn, ownership dispersion, and more. Zero LLM calls; pure local analysis. The weights are calibrated against a real defect corpus, so a low score means more likely to harbour bugs, not just bigger.

Pick the mode by what you pass

• Dashboard — get_health() (no targets): a directive naming what to fix first, then repo-level KPIs and the lowest-scoring files. Start here for "how healthy is this codebase?" or "what should we clean up?".
• Targeted — get_health(targets=["src/x.py", "src/y.py"]): per-file score and the specific marker findings driving it. Use before/after a refactor, or to explain why a file is flagged.

Useful include flags