  While model checking PCTL for Markov chains is decidable in polynomial-time,
the decidability of PCTL satisfiability, as well as its finite model property,
are long standing open problems. While general satisfiability is an intriguing
challenge from a purely theoretical point of view, we argue that general
solutions would not be of interest to practitioners: such solutions could be
too big to be implementable or even infinite. Inspired by bounded synthesis
techniques, we turn to the more applied problem of seeking models of a bounded
size: we restrict our search to implementable -- and therefore reasonably
simple -- models. We propose a procedure to decide whether or not a given PCTL
formula has an implementable model by reducing it to an SMT problem. We have
implemented our techniques and found that they can be applied to the practical
problem of sanity checking -- a procedure that allows a system designer to
check whether their formula has an unexpectedly small model.
