Exactly, it misses out on explaining how the fixed Huffman table is interpreted to apply symbol and distance codes, or how dynamic tables are derived from the input itself. Sure it's the hardest part, but also the more interesting to visualize. As another commenter pointed out, we are just left with mysterious bit sequences for these codes.
Even if it doesn't use block-based compression, if there isn't a huge range of corrupted bytes, corruption offsets are usually identifiable, as you will quickly end up with invalid length-distance pairs and similar errors. Although, errors might be reported a few bytes after the actual corruption.
I was motivated some years ago to try recovering from these errors [1] when I was handling a DEFLATE compressed JSON file, where there seemed to be a single corrupted byte every dozen or so bytes in the stream. It looked like something you could recover from. If you output decompressed bytes as the stream was parsed, you could clearly see a prefix of the original JSON being recovered up to the first corruption.
In that case the decompressed payload was plaintext, but even with a binary format, something like kaitai-struct might give you an invalid offset to work from.
For these localized corruptions, it's possible to just bruteforce one or two bytes along this range, and reliably fix the DEFLATE stream. Not really doable once we are talking about a sequence of four or more corrupted bytes.
It would be cool if we could supply our own Huffman table and see how that affects the stream itself. We might want to put our text right there! https://github.com/nevesnunes/deflate-frolicking?tab=readme-...