During April 2026, Momreda Reda developed a Smart Dataset Loading feature for the neuroinformatics-unit/movement repository, focusing on improving dataset loading robustness and user experience. Using Python, they refactored the loading pipeline to automatically detect and select compatible loaders for various file formats, reducing manual configuration and minimizing user errors. Their approach included enhanced error handling, raising explicit ValueErrors when the source software could not be inferred, and updating documentation to reflect these changes. By incorporating unit testing and edge-case coverage, Momreda improved the maintainability and reliability of the data processing workflow, demonstrating thoughtful engineering within a focused project scope.