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I don't think this approach is wise.

Concentrate on code quality, and whether it does what it needs to do. Not whether it was written by AI or not.

Thanks, I actually concentrated on improving code quality, the patterns I flagged are poor design choices that humans wouldn’t write. Examples are duplicated functions doing same thing, dead or redundant codes etc. These builds up and degrade the codebase over time.

> ...are poor design choices that humans wouldn’t write.

They certainly do in my experience. Maybe you've been lucky and haven't worked with really messy programmers.

I have worked and seen these in code reviews but the issue now is code reviews are overwhelming and non existent in some cases.

I'm interpreting this not as a "catch ai submissions gotcha" tool, but as a "last pass in review catch mistakes AI made that i may have missed" tool. Having more linters is a good thing IMO (I say this as someone who doesn't use AI to generate code, but works with people who do and has to review a lot of AI generated code)

Exactly, that’s what it does. You can see the tool as a quality gate you put in place to ensure that any AI generated code meets a standard.

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