I don't think this approach can work.

Anyway, I've written a library in the past (way way before LLMs) that is very similar. It validates stuff and outputs translatable text saying what went wrong.

Someone ported the whole thing (core, DSL and validators) to python a while ago:

https://github.com/gurkin33/respect_validation/

Maybe you can use it. It seems it would save you time by not having to write so many verifiers: just use existing validators.

I would use this sort of thing very differently though (as a component in data synthesis).