The quality is good and it's giving you all of the maps (as well as the .blends!). It seems great for its stated goal of generating ground truth for training.
However, it's very slow/CPU bound (go get lunch) so probably doesn't make sense for applications with users behind the computer in the current state.
Additionally, the .blend files are so unoptimized that you can't even edit them on a laptop with texturing on. The larger generations will OOM a single run on a reasonably beefy server. To be fair, these warnings are in the documentation.
With some optimization (of the output) you could probably do some cool things with the resulting assets, but I would agree with the authors the best use case is where you need a full image set (diffuse, depth, segmentation) for training, where you can run this for a week on a cluster.
To hype this up as No Man's Sky is a stretch (NMS is a marvel in its own right, but has a completely different set of tradeoffs).
EDIT: Although there are configuration files you can use to create your own "biomes", there is no easy way to control this with an LLM. Maybe you might be able to hack GPT-4 functions to get the right format for it to be accepted, but I wouldn't expect great results from that technique.