During April 2025, work focused on enhancing the faker-js/faker repository by introducing localized gender data for the Chinese zh_CN and zh_TW locales. This involved creating dedicated data files and integrating them into the locale definitions, enabling culturally relevant data generation for Chinese-speaking users. The approach emphasized structured data modeling and careful data file management using TypeScript, with a clear commit-driven workflow to ensure maintainability. By expanding locale coverage and improving the realism of generated data, the changes addressed the needs of enterprise clients requiring robust internationalization and localization, ultimately supporting higher user satisfaction in Chinese market deployments.