Let an AI clear out your false positives without letting it hide a real bug

Last time I wrote about wiring up a security gate that blocks merges in CI with .

• Star it if the "AI proposes, Go and a second model confirm" direction is one you want to follow.


• Run it against your own LLM endpoint and tell me what happened: which model refutes well, which one likes to make things up. Feedback from a real model is the most useful kind.


• The verifier's adversarial prompt, the driver vocabulary, the consensus threshold: it all lives in internal/usecase/fptriage, and it's short and easy to read.

If you turn this on in your own repo, drop a comment with how many false positives the AI held back on the first run, and whether it ever came close to refuting something that turned out to be real. I'm curious.