Honestly...sounds like something an AI agent could do pretty well. Then when you're browsing the library and you find a mistake you can fix things as needed.

Weigh the environmental cost against how much you value your time. Using local LLMs is probably enough for this kind of job, with much smaller environmental cost.

If you're going to do it by hand anyway, you could add the missing tracks to Musicbrainz. This way Picard would be able to recognize them, for you and for everyone else.

Make a cup of tea, open mp3tag and get to work!

My routine for that is about what you would expect, Coffee, listen to the track, Research it, Manually fill out as much of the tag as I can, upload to MusicBrainz, Repeat.

Each album takes an hour or two. Faster if I can find a page somewhere with the whole album listing, preferably including the names of everyone involved with the album.

There isn't an easier way that I've found.

Every few days I'll have Picard rescan the collection in the unlikely event someone else has also worked on some of the tracks I'm working on. It does happen, not very often, but it does happen.

Sometimes it just don't find the audio fingerprint. Try the lookup button instead. Or fill in the missing info by hand. Btw I usually use the --embed-metadata flag on yt-dlp. Most tags should fit like that.