Varshaa developed a comprehensive quality control reporting tutorial for the mne-tools/mne-python repository, focusing on M/EEG data analysis workflows. The tutorial guides users through raw data inspection, event detection, epoching, and ICA-based artifact inspection, providing an end-to-end reproducible QC process. Implemented in Python using MNE-Python, the work emphasizes data analysis, quality control, and report generation. Varshaa collaborated with Eric Larson and leveraged automated CI tools to ensure robust documentation and code quality. This contribution addressed the need for clearer, more reproducible QC pipelines, enhancing onboarding for new users and supporting developers with a reusable, well-documented workflow.