The automated nature of ULaMDyn streamlines the traditionally manual and labor-intensive task of postprocessing NAMD data, making it highly scalable for large systems and long timescale simulations. Beyond its current capabilities, the package is set to in corporate more advanced descriptors like MBTR and clustering techniques like DBSCAN, further enhancing its applicability to diverse molecular systems. With these upcoming features, ULaMDyn has the potential to significantly broaden its impact, facilitating the study of complex excited-state processes in areas ranging from photochemistry to materials science.