Precise genome editing technologies have been readily developed in the past decade. In particular, base editor, a CRISPR/Cas9 derivative that enables single base substitution, and prime editor, another CRISPR/Cas9 derivative that enables base substitution and short insertion and deletion, show great prospects in gene therapy applications. With the advancement of the technology, the precision of these editors have been greatly improved, generating custom edits to the genome while creating few by-product edits. Detection of the editing events has been primarily relied on deep sequencing on individual samples. However, due to the high cost in manpower and resources, use of deep sequencing technology for large-scale screening and engineering of individual genome editor’s performance remains impractical. In this study, we develop a reporter system by coupling artificial gRNA targets with precise genome engineering tools on the same construct. With proximal placement of the gRNA targeting region and the coding sequence of the editors, the phenotype (editing outcomes) and genotype (editor variants) can be presented on a single DNA fragment upon amplification from the genome. This enables high-throughput multiplexed deep sequencing of a pooled library. Further introduction of restriction enzyme sites on the gRNA targets allows rapid detection of genome editing events by restriction fragment length polymorphism and Sanger sequencing. This work demonstrates the use of our reporter system in functionally characterizing a 5’UTR library, from which a 5’UTR sequence was identified to enhance the cytosine base editor’s editing activity. This work further explores the potential to couple our reporter system with CombiSEAL, a method that enables assembly and barcoding of an engineered protein library with different domain combinations, for high-throughtput engineering of genome editors. With this, results presented in this study have successfully established the association between the barcodes, the engineered cytosine base editor variants, and the editing outcomes, from which we reveal the wide range of editing activity and accuracy of different base editor variants. This work also extends the application of our reporter system for screening prime editing events, demonstrating its transferable performance in other precise editing tools. Together, we envision our reporter system can be applied for high-throughput engineering precise genome editing tools in the future. The 5’UTR screen dataset generated in this work also provides insights for future machine learning studies to decipher the relationship between 5’UTRs and protein expression.