What are commonly classed “probabilistic graphical models” are a very particular subset of probabilistic models, namely those faithfully specified as directed acyclic graphs. Another common class of graphical models are those faithfully specified as undirected graphs. The overlap between these two classes is only partial, with some models faithfully specified by one, both, or none. Additionally there are generalizations of graphical models to expand the scope of faithful representations. See Bishop 8.3.4.
The Stan language goes beyond all of this by requiring only a density representation. Converting a Stan program into a graphical specification will be well-posed only if the model falls into the domain of the corresponding graph type, and then implementable only if one can identify that correspondence in finite time.
The problem with heuristic translations beyond their heuristic nature is that they confuse the intent of the Stan language. If we wanted a pure graphical language then we would have written an entirely different language. Indeed this is the approach that BUGS, PyMC, and others have taken which is why they have such tools.
In my opinion throwing down incomplete heuristics without a hell of a good UX that is able to communicate what the graphical model representation means and what it doesn’t mean is only going to confuse users and hence will be more danger than benefit. And I haven’t seen any discussion of such an UX at all.