Developed an image-rich scraping enhancement for the cssgunc/beautiful-together-next repository, focusing on elevating media coverage for adoptable dogs and cats. Leveraging Python, BeautifulSoup, and Requests, the work introduced dedicated scraping paths and functions to extract, filter, and persist image data separately from general scraping logic. The database schema was extended using Supabase to store image assets, enabling richer animal profiles and improved analytics. This refactoring reduced technical debt by clarifying responsibilities within the codebase and set a foundation for future image quality controls. No bugs were fixed during this period, with efforts concentrated on robust feature delivery and maintainability.