Judging code quality by use of LLM in a documentation and commit messages is weird.

While I write all of my code myself and I'm against vibe coding etc., there is one place where I let a LLM write for me: readmes, commit messages and Javadoc comments.

I know how to write code but at the same time I'm shit at both my native language and even more so at English. So I let Language Models write natural language texts for me and just fix them when necessary. My documentation is more clear, grammatically correct and more detailed than in any of my previous projects, and I can focus on writing code.

And I wouldn't say "No one does that in a project they're building for themselves". I do that for projects that only I will ever see, and OP shared his project with others, so it's great that he included a clear documentation

No one does that in a project they’re building for themselves.

Speak for yourself, I always did that and I found it easier with LLMs nowadays.

I hate most AI shite with a passion but when it helps my colleagues write commits which are more than "add stuff", "fix some things" I'm fine with it.

I rarely use AI to generate code, usually only when I need a starting point. It's much easier to unfuck AI code than to stare blankly at a screen for an hour. I'd never commit code I don't fully understand or have read to the last byte.

I hope OP is doing the same. LLMs fail at 90% of coding tasks for me but for the other 10% (mostly writing tests, readmes, boilerplate) it's really OK for productivity.

Ethics of LLMs aside, if you use them for exactly what they're built for – being a supercharged glorified autocomplete – they're cool. As soon as you try to use them for something else like "autocompletion from zero" aka "creativity", they fail spectacularly.

I answered earlier, that I use AI and this is just a commit skill for an agent.