It appears that the molecules on the page are generated with a machine learning algorithm trained on a small organic molecules dataset that is heavily biased towards cyclic, particular nitrogen heterocyclic, structures (I only sampled about 40 of them, so it could also have just been my luck).

The model seems to have learnt chemistry pretty well because, as many have already pointed out, most of the molecules generated do actually exist (or are extremely likely accessible if they haven't already been documented). Even the ones with strange bond angles have otherwise perfectly normal number of bonds. The only time where I get molecules that cannot possibly exist are those with overlapping atoms that just defy known physics.

Addendum: it is worth noting that the model might actually have been trained with data that contain bond lengths, or even spatial information if no post-generation geometry optimisation is performed before a molecule is rendered.