AI code review tool for GitHub: start with least privilege

Use a test repository and a pull request containing one known defect. Review the workflow permissions and check whether the job needs write access to report a result. Keep an approving maintainer in the merge path. Do not expose repository secrets to untrusted pull-request code to make a reviewer run.

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.