The property of fitness-for-purpose states whether running a software component with a supplied set of inputs can satisfy a given goal. Our interest is to assess whether a chosen problem solver, together with one or more knowledge bases, can satisfy a given problem-solving goal. In general, this is an intractable problem. We therefore introduce an effective, practical, approximation to fitness-for-purpose based on the plausibility of the goal. We believe that constraint (logic) programming provides a natural approach to the implementation of such approximations. We took the Common LISP constraints library SCREAMER and extended its symbolic capabilities to suit our purposes.