The skeletonisation methods of 3D object models gained noteworthy attention in recent years and have been extensively investigated, inspired by their wide-range applications, including computer graphics and robotics. However, there remains a gap that the quantitative reference of high-quality skeletonisation results is hardly given by the previous studies. Building upon previous research on point cloud skeletonisation, this paper explores the inherent characteristics of the skeletonisation process across objects of varying shapes. This analysis aims to provide intuitive insights into the quality of the resulting desirable skeletons. Additionally, we introduce a new concept of stable convergence of contraction based on distributions of geometric curvature and vectorial normal changes.