In this work we describe the design and implementation of a general framework for visualizing and editing motion planning environments, problem instances, and their solutions. The motion planning problem consists of finding a valid path between a start and a goal configuration for a movable object. The workspace is, in traditional robotics and animation applications, composed of one or more objects (called obstacles) that cannot overlap with the robot. As even the simplest motion planning problems have been shown to be intractable, most practical approaches to motion planning use randomization and/or compute approximate solutions. While the tool we present allows the manipulation and evaluation of planner solutions and the animation of any path found by any planner, it is specialized for a class of randomized planners called probabilistic roadmap methods (PRMs). PRMs are roadmap-based methods that generate a graph or roadmap where the nodes represent collision-free configurations and the edges represent feasible paths between those configurations. PRMs typically consist of two phases: roadmap construction, where a roadmap is built, and query, where the start and goal configurations are connected to the roadmap and then a path is extracted using graph search techniques.