In response to organizational restructuring, West Virginia University's Metadata Unit streamlined quality control workflows for a more distributed team of cataloging staff by running python scripts on raw MARC delivered by a query collection. The scripts deliver a count of each cataloger's new and edited bibliographic and holdings records, and provide a selection of fields relevant to their current projects in a spreadsheet that can be easily reviewed and used to assign manual corrections. API calls to execute corrections could also be integrated easily into these scripts. I will provide line by line explanation of code, which uses pandas, pymarc, and SQLite in a Google Colab environment on data accessible to any WorldShare Management Services (WMS) subscriber, and I will reflect on how the scripts assisted with change management during a large, organizational transition.