This dataset illustrates the Best Practices in flow cytometry for studying phytoplankton, using CytoSense (CytoBuoy, NL) types of flow cytometers. The use of flow cytometry to collect datasets on phytoplankton functional groups is rapidly expanding worldwide with monitoring laboratories or deployments on scientific vessels and autonomous environmental monitoring platforms. Automation, coupled with enhanced autonomy, improves the resolution of the spatial and temporal distribution of phytoplankton. Sharing these datasets with the scientific community—whether to improve the resolution of global phytoplankton distribution or to facilitate the intercomparison of environmental indicators among monitoring laboratories requires quality-controlled instruments and standardised data acquisition. Although CytoSense types of flow cytometers all operate on the principle of recording the optical pulse shapes of particles passing through a laser beam, their configurations vary in terms of laser wavelength and power, sample inlet, and dataset output format. The characterisation of phytoplankton communities and their optical representation on cytograms has been standardised by experts, with resolution depending on the optimal configuration of the instrument in use. This dataset exemplifies the application of best practices for optimising the settings of pulse shape-recording CytoSense flow cytometers. We address key aspects such as particle counting limits, the coincidence phenomenon, trigger threshold and PMT voltage optimisation, and regular quality control procedures, illustrating these principles with datasets from two types of instruments. The primary goal is to establish a methodological framework that guides and supports the exploration and application of this type of flow cytometer, ultimately achieving reliable and optimal sample acquisition resolution.