Shinyscreen was designed to fill the niche in-between. Its focus is exclusively on data exploration, visualisation and automated quality control combined with manual overrides to offer simple but powerful functionality without the complexity of the advanced workflows. Unlike other tools that give user unrestricted access to raw MS data -the vast majority of which is irrelevant for a particular investigative effort -the Shinyscreen approach is centered on a preselected list of compounds or masses of interest. Thus, it can be used to support a wide variety of HRMS workflows, including target, suspect ("known") and NTA ("unknown") data interrogation without a confusing array of options that can overwhelm inexperienced users and students learning the basics of data processing. This paper introduces Shinyscreen as a versatile and user-friendly interface for high-throughput HRMS data quality control, discussing the design principles, and demonstrating its utility through real-world applications. By bridging the usability gap between low-level programming tools and complex, resourceintensive platforms, Shinyscreen empowers researchers to focus on their investigative goals, enhancing both accessibility and efficiency in MS data exploration, while also serving a role in teaching activities at the University.