
Won Kim contributed to the JumboCode/bread-and-roses repository by building and enhancing admin-facing features for event scheduling and volunteer management. Over two months, he implemented a Custom Day Events admin overview that displays upcoming days with custom opening and closing times, volunteer session data, and per-day volunteer counts, using React and Next.js with TypeScript and CSS. He refined date calculations and data-fetching logic to improve reliability and performance, and introduced future-only event scheduling to prevent same-day events. Won also improved dashboard usability by adding friendly empty states for volunteer lists, demonstrating thoughtful attention to both backend logic and user experience.
May 2025 – JumboCode/bread-and-roses: Focused improvements in deployment signaling, event scheduling logic, and dashboard UX, delivering reliability gains and a smoother admin experience.
May 2025 – JumboCode/bread-and-roses: Focused improvements in deployment signaling, event scheduling logic, and dashboard UX, delivering reliability gains and a smoother admin experience.
April 2025 monthly summary: Implemented major Custom Day Events admin enhancements in JumboCode/bread-and-roses. Delivered an Admin Overview that shows upcoming days with custom opening/closing times, volunteer session data, and per-day volunteer counts; added optional titles for custom day events and updated EventCard to display titles when present. Refined date calculations and data-fetching logic for custom day data to improve reliability and performance. This work improves admin planning, data accuracy, and end-user clarity.
April 2025 monthly summary: Implemented major Custom Day Events admin enhancements in JumboCode/bread-and-roses. Delivered an Admin Overview that shows upcoming days with custom opening/closing times, volunteer session data, and per-day volunteer counts; added optional titles for custom day events and updated EventCard to display titles when present. Refined date calculations and data-fetching logic for custom day data to improve reliability and performance. This work improves admin planning, data accuracy, and end-user clarity.

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