Backend Models

Enforcing coding standards for backend models ensures consistency across your data layer by applying AI-guided checks to model definitions, naming conventions, field types, and relationship structures. Apply this Skill to review files where backend models are defined or used, including model definitions, data access layers, and API interfaces, to align with your repository guidelines.

Database model design balances efficiency, scalability, and maintainability through consistent naming conventions, proper data type definitions, and well-defined relationships. This Skill applies AI-driven consistency checks to help create models that scale across development, testing, and integration workflows while adhering to repository coding standards.

Yes. This Skill standardizes backend data models across microservices by enforcing consistent naming conventions, field types, and relationship definitions. When defining new models for a microservice, apply it to ensure alignment with established data layer standards and promote a cohesive architecture.

Data model definitions must satisfy requirements for adherence to repository coding standards and consistent interface contracts. This Skill applies automated checks to model definitions and data access layers, verifying alignment with naming conventions, documentation standards, and integration guidelines your team has established.

When reviewing backend model consistency, check structure and field definitions, naming convention alignment, data type uniformity, relationship definitions, and documentation alignment with repository guidelines. This Skill automates these checks across model definitions, data access layers, and API interfaces in your workflow.