The last decade has witnessed a massive expansion in the toolset available for genome editing that paves the way for new therapies, diagnostics and technologies. Since overlapping tool classes (e.g. nucleases, base editors and prime editors) enable targeted deletion, substitution or insertion of DNA, genome engineers must select an optimal tool for any given goal. Unfortunately, benchmarking tools from different classes against one another is challenging, due to their differing modes of action. Even so, they all suffer a similar weakness – the ability to accurately identify their genetic targets and install their intended edit. This PhD project aims to establish a generalized, high-throughput strategy for benchmarking these criteria within and across tool classes, thereby non-ambiguously characterizing and establishing their suitability for genome editing. Success relies on the student’s ability to implement and integrate biochemical, computational, cellular and bioinformatic approaches.