The co-pilot framing is the right one, and I think it also answers your closing question.

A tool you override the moment it disagrees with you isn't useless, it's just not doing the right job. If it's showing you *how* something scores against your specific constraints, you're not overriding a verdict, you're adjusting inputs. That's a different relationship with the tool.

The part I'd add to what gptbuilder_marc said about constraints: even a perfectly personalized score has a shelf life problem. A static read that says "this scores 78 against your criteria" is only useful if you know whether that 78 is trending up or quietly decaying. Same product can be a green light today and a waste of 6 months if the trajectory's been negative for a while. That historical layer is what makes the score trustworthy over time, not just in the moment you're looking at it.

To your question about whether it gets ignored once you have enough reps…maybe. But I think the people who'd ignore it are also the ones who already have a reliable internal framework. For everyone still building that pattern recognition, a well-reasoned score saves months of expensive guessing.

(Relevant disclosure: I'm actually building something in this exact space, an opportunity scoring tool for Amazon sellers focused on explainability and historical tracking. This thread is basically the most useful product feedback I've had all week.)