A grammar is really just a special case of the more general issue of how to pick a single token given the probabilities that the model spits out for every possible one. In that sense, filters like temperature / top_p / top_k are already hacks that "do the work" (since always taking the most likely predicted token does not give good results in practice), and grammars are just a more complicated way to make such decisions.