Find the files most likely to break. Before they do.

Every file gets a single 1 to 10 score computed from 25 deterministic markers: McCabe complexity, deep nesting, brain methods, class cohesion (LCOM4), god classes, Rabin-Karp clone detection, change entropy, co-change scatter, ownership dispersion, prior-defect history, test-quality smells, and more. Lower scores mean the file is more likely to harbor defects.

It is defect-validated. On the same 2,770 files across 9 languages with real defect labels, ranking by repowise health surfaces 2.3x the defects of a leading commercial tool under the same review budget (recall 0.173 vs 0.074, effort-aware Popt 0.607 vs 0.462, ROC AUC 0.731 vs 0.705). Across 21 open-source repos the mean cross-project ROC AUC is 0.74 with a 95% confidence interval of 0.68 to 0.79, ranging from 0.55 to 0.86 across individual repos.

No. Scoring is fully deterministic: 25 markers with weights calibrated offline against a defect corpus. Only the learned constants ship, so the same code always produces the same score, in under 30 seconds on a 3,000-file repo. No cloud, no API calls, no drift.

Both score code health, but repowise is open source so every heuristic is inspectable and reproducible on your own repo, and the score ships inside a broader platform: an architecture-aware wiki, git intelligence, architectural decisions, agent provenance, and ten MCP tools for AI agents. repowise does not offer AI auto-refactoring.

No. The discrimination survives controlling for file size (partial Spearman rho of -0.16) and significantly out-discriminates both recent churn (+0.10 AUC) and prior-defect history (+0.12 AUC), with DeLong p below 1e-9.

Yes. repowise ingests LCOV and Cobertura coverage to compute untested-hotspot risk (the intersection of low coverage and high hotspot score), alerts when a file's health starts declining, and ranks refactoring targets by impact for effort.

Yes, that is the point. Every heuristic is open source under AGPL-3.0, and the validation runs on your own repo. On a typical project, 16 of the 20 lowest-health files had a bug fix in the last 6 months, 3.3x the 24% baseline.

Yes, as a static health pillar, not as an APM or profiler. repowise statically detects performance-risk shapes such as N+1 access and IO-in-loop patterns and scores them as a co-equal third pillar alongside defect risk and maintainability. It is high precision and low recall by design: it raises few findings, but the ones it raises are real. There is no runtime, no agent, and no tracing; it reads your source, like every other signal.

No, and that is deliberate. repowise ranks refactoring targets by impact for effort and alerts you when a file's health starts declining, but it hands you a human-readable, deterministic worklist; it does not open PRs or rewrite your code. The suggestions are template-based and inspectable, with no LLM editing your repo.