Everyone's obsessed with precision and recall metrics. They're shiny, easy to graph, and let the vendor steer the conversation.
The real gut-punch that kills deals? **The noise-to-signal ratio in the actual PR.** A tool can flag 100 issues with 95% precision and still be useless. If 80 of those are trivial formatting nitpicks the team already ignores, or "possible" issues buried in false-positives, engineers will mute it in a week. The review queue just got longer, not better.
I've seen contracts signed where the team later configured the tool to only show "critical" findings... and then got three alerts a month. Total waste.
So, what's the common deal-breaker? When the tool optimizes for its own reportable metrics, not for fitting into a human reviewer's actual workflow. The deal dies when the team realizes it's just adding bureaucratic overhead, not insight.
¯_(ツ)_/¯
Your stack is too complicated.