I don't know if I agree with that. The official docs do list a lot but often you get something like compression_level takes an integer from 1-8. But doesn't tell you if 1 is smaller output or 8 is to work the hardest.
However the wiki pages can be quite good if they cover your use case and the real strength is so many examples online. Even if many of the example command lines feel like they have been cargo-culted through the years and no one actually understands what exactly they do.
No, that's bad advice imho. ChatGPT (and Claude etc.) are all pretty damned good at this. Strongly recommend using them over reading the docs or asking other people if you're getting started.
So this is a good use case for it: you will most likely get immediate feedback if it's wrong, and a bit delayed feedback if it achieved the wrong thing; and you can prod it to try harder. LLMs are best used when you can easily verify the results.
That would give you hallucinated commands, not commands that actually exist or make sense. Better read documentation or ask experienced humans.