AI code review tool: evaluate evidence before accepting a finding

A useful finding identifies the affected code, explains a reproducible failure and suggests a change you can review. Ask the tool to distinguish a demonstrated defect from a style preference or an uncertain hypothesis. Confirm the result with a focused test before merging a fix.

Build a small evaluation set

1. Record one failing behavior and the expected result.
2. Add a similar clean case to expose false positives.
3. Run the checker and retain the exact version and output.
4. Review any proposed fix and rerun the regression test.

Keep adoption reversible

Start in an advisory mode while you understand the findings. Decide which checks merit blocking a merge, document exceptions and keep source access limited to what the workflow needs. See the BugClass documentation for the current detector and integration scope and the pricing page for current availability. This page makes no claim that a particular detector catches every bug in its category.