Classifying objects in computer vision, we are faced with a great many features one can use. This paper argues that diagrammatic representations help to comprehend properties of features. This is important for the purpose of deciding which features should be used for a given classification task. We introduce such a diagrammatic representation for a shape feature and show how it enables one to decide whether this feature helps to distinguish some categories given. Additionally, it shows that the proposed feature keeps up with other features falling into the same complexity class.