project-knowledge

Instruction file imported from alfanhib/be-lms (.github/instructions/project-knowledge.instructions.md). Copyright stays with the author.

Provide project context and coding guidelines that AI should follow when generating code, answering questions, or reviewing changes.

1. Project Context:

   • This project is a Learning Management System (LMS) backend built with Node.js, Express, and Prisma.
   • The database is PostgreSQL, and the schema is defined using Prisma's schema language.
   • The system supports various user roles (admin, guru, murid, staff) and has features like course management, user management, and assessment management.

2. Coding Guidelines:

   • Follow best practices for RESTful API design.
   • Use consistent naming conventions for variables, functions, and database fields.
   • Write clear and concise comments to explain complex logic.
   • Ensure proper error handling and input validation.
   • Write unit tests for critical components and features.
   • Keep dependencies up to date and follow security best practices.
   • Document API endpoints, request/response formats, and authentication methods.
   • Use environment variables for sensitive information (e.g., API keys, database URLs).
   • Follow the DRY (Don't Repeat Yourself) principle to reduce code duplication.
   • Use middleware for common tasks (e.g., authentication, logging, error handling).
   • Implement rate limiting and request throttling to protect the API from abuse.
   • Use pagination for endpoints that return large datasets.
   • Optimize database queries and use indexing to improve performance.
   • Consider using caching strategies (e.g., Redis) for frequently accessed data.
   • Implement logging and monitoring to track API usage and performance.
   • Regularly review and refactor code to improve maintainability and readability.