
Developed the end-to-end MentalForm feature for the NYCU-Service-Learning/nanao-system repository, focusing on reliable mental health data capture and retrieval. Leveraging TypeScript, NestJS, and Prisma ORM, the work introduced a robust database schema and comprehensive API endpoints to support form submission and analytics. The implementation included new modules, controllers, services, and DTOs, establishing a modular backend architecture designed for scalability and future extension. By prioritizing data integrity and maintainability, the solution enables seamless integration into care workflows and supports advanced analytics. No major bugs were reported during the development period, reflecting a stable and well-structured engineering approach.
November 2024 monthly summary for NYCU-Service-Learning/nanao-system. Key focus: delivering end-to-end MentalForm functionality and establishing a scalable foundation for mental health data capture. No major bugs were reported this month. The work enhances data integrity, enables analytics, and supports care workflows by introducing a Prisma-backed data model and a robust API surface.
November 2024 monthly summary for NYCU-Service-Learning/nanao-system. Key focus: delivering end-to-end MentalForm functionality and establishing a scalable foundation for mental health data capture. No major bugs were reported this month. The work enhances data integrity, enables analytics, and supports care workflows by introducing a Prisma-backed data model and a robust API surface.

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