Worked on enhancing the developer documentation for high-dimensional inference methods, specifically Desparsified Lasso and its clustered variants, within the lionelkusch/hidimstat repository. Focused on improving clarity and usability, the updates included refined code snippets, typo corrections, and a refreshed changelog to better support researchers working with high-dimensional data analysis. Leveraged Python and skills in data analysis, documentation, and statistical modeling to ensure the documentation accurately reflected the underlying methods. The work aimed to streamline onboarding and reduce support needs by making technical concepts more accessible, with collaborative contributions to maintain accuracy and consistency across the documentation and related files.