We describe the conception of a visualization and transformation tool for traces of the real-time strategy (RTS) computer game StarCraft. The development of our tool StarTrace is driven by the domain the traces originate from as well as the observable elements those traces contain. We elaborate on those influences, which also include both the structure of the existing game traces and the requirement to use these traces to improve the performance of an machine learning (ML) agent that attempts to learn to play parts of the game.