In this study, we have meticulously assessed the reproducibility and reusability of MIST for the prediction of chemical fingerprints from MS data. Our endeavors to replicate the training and fingerprint prediction of MIST were largely successful, albeit not without encountering several minor challenges. These challenges, including small bugs in the source code and occasional gaps in the documentation, underscore the inherent complexities involved in developing advanced bioinformatics tools. Despite these hurdles, the overall good quality of MIST's documentation and source code facilitated the resolution of these issues, albeit requiring expert effort. This experience demonstrates the significant disparity between the development of a research prototype and the refinement of a tool to a production-ready state, emphasizing the necessity for robustness to ensure successful application across varied scientific environments. The absence of tests within the MIST code repository further highlights this gap, suggesting that the integration of software engineering best practices could greatly enhance the development process, ensuring the production of high-quality scientific software while saving time in the long term.