June 2026: Delivered documentation and attribute validation for mne.Annotations to improve reliability and developer experience. This work clarifies how onset, duration, description, and ch_names should be used and ensures attributes are properly managed within the class, reducing misconfiguration risks in downstream analyses.

May 2026: Delivered Docker build optimization and CI/environment compatibility for google-gemini/gemini-cli, achieving smaller images and faster builds while ensuring reliable deployments in environments without a git history. This included a multi-stage Docker build, a .dockerignore to prune build context, and environment-variable based git metadata in scripts. The changes enhance reproducibility, CI reliability, and deployment speed across diverse environments.

April 2026 (mne-tools/mne-python) delivered two focused updates that improve visualization reliability and API clarity for MEG workflows. A bug fix ensures plot_topomap sensor names align with the Info object data, particularly for MEG with gradiometers, improving interpretability and reducing plotting errors in published analyses. A feature-quality enhancement maps public mode names to internal identifiers in get_point_spread and get_cross_talk, exposes hidden modes, and adds input validation to prevent invalid usage. The changes enhance data integrity, user experience, and maintainability across core visualization and analysis tools.

March 2026 monthly update: Delivered targeted enhancements and fixes across mne-python and gemini-cli, driving reliability, usability, and accessibility. Key user-facing features include robust documentation for epoch/montage handling and a new reset_first_samp option after cropping, alongside screen reader accessibility for RewindViewer. Critical fixes addressed indexing and attribute handling bugs in montage sources, and spacing logic in SourceMorph, reducing runtime errors and ensuring consistent behaviors. These contributions strengthen our core data processing flows, improve developer and end-user experience, and demonstrate solid Python, documentation, and testing practices.