We use Monte Carlo steps to measure the frequency of every accessible pore sizes binned by 0.1 Å and to generate a histogram of pore sizes (or pore size distribution, PSD). This histogram then generates descriptors based on statistical parameters describing the overall location, the dispersion, the shape and the modality of the distribution. In addition to the mean and standard deviation of the distribution, we introduce two additional moments: the skewness (𝛾), corresponding to the third standardized moment, measures the asymmetry of a distribution; and the kurtosis (𝑘), being the fourth standardized moment, measures the relative weight of the distribution's tails. Recognizing the importance of characterizing the number of different pore sizes that are likely to have contributed to the observed selectivity drop, we try to find a simple descriptor for measuring the number of modes in the distribution. The Sarle's bimodality coefficient, BC = (𝛾 2 + 1)/𝑘, provides a simple quantification of the extent to which the distribution deviates from unimodality by considering only skewness and kurtosis. Finally, to assess the diversity of pores, we introduce an effective number 𝑛 eff = 𝑁 2 / ∑︀ 𝑛 2