Samuel Halverson developed a core data processing enhancement for the Keck-DataReductionPipelines/KPF-Pipeline repository, focusing on improving the workflow for SM-targeted reductions. He updated the WLS files for each SM, leveraging Python and his expertise in data processing and pipeline development to increase both the speed and reliability of data handling. This work improved the overall functionality and performance of the pipeline, resulting in higher data quality and faster turnaround for scientific outputs. By refining the data processing capabilities, Samuel enabled more consistent and timely results for SM observations, directly supporting researchers in achieving more efficient and accurate analyses.