We developed a new Python software tool that standardises and automates the analysis of data from a cloud simulation chamber. It identifies ice-forming particles in the atmosphere and ensures consistent data quality through built-in checks, making results more comparable across studies. We also analysed measurement data to provide recommendations for improving instrument reliability and long-term monitoring of atmospheric ice-forming particles. This helps to better understand how clouds behave.