Code metrics in general aren’t that widely used. I’ve only ever worked at one place (a bank) that tracked it, and that was only because sonarcube had it built in.

While a lot of metrics make intuitive sense, we don’t have that much hard evidence to prove or disprove their value. Part of it is the whole “if a metric becomes a target, it ceases to be a good metric” thing. Adding the checks to a large existing project probably has negative value. But I think it’s worth doing for greenfield projects.

For humans, these should just be advisory. But for LLMs I’m happy enough to make it a blocking check.

I keep thinking of doing an experiment where I give the same LLM the same problem, and only change which metric is enforced. And then see if any of them have a noticeable effect on correctness/maintainability.

> any examples of how people get this into an actual report / CI test / benchmark / whatever ?

Yeah they have examples of adding it to CI, or local checks, generate html reports, etc in their docs.