Worked on the ml-explore/mlx repository to enhance documentation quality, focusing on the Transform vmap and lazy evaluation sections. Addressed documentation errors, corrected typos, and clarified example indexing and in_axes references to reduce user confusion and support queries. Used Python and reStructuredText to implement these improvements, ensuring that onboarding materials are clearer and that transform-based workflows are safer for users. Demonstrated attention to documentation hygiene and version-control discipline, which supported smoother team collaboration. The work resulted in more accurate and accessible documentation, directly impacting user experience and reducing the likelihood of misunderstandings in the mlx project’s technical guides.