During February 2026, Truc Nguyen developed a data readiness reporting enhancement for the APPFL/APPFL repository, focusing on the Cora dataset’s client training indices. Truc refined the data pipeline to generate more informative readiness reports and introduced robust error handling to reduce workflow failures during machine learning training. The work incorporated code review feedback to improve maintainability and readability, laying the foundation for scalable reporting in future Cora training workloads. Utilizing Python, PyTorch, and data analysis techniques, Truc’s contribution improved reliability and visibility in client training processes, enabling faster troubleshooting and smoother training pipelines without addressing major bugs during this period.