zeta-api-endpoint

To scaffold a FastAPI endpoint, this skill automates the Router → Service → Repository pattern, generating Pydantic models, service logic, and API route definitions to ensure proper input validation and business logic implementation.

The best way to add Pydantic models and service logic is by using this skill, which automates boilerplate creation and enforces established architectural patterns for backend development tasks within the financial analysis platform.

Yes, you can use this skill to generate FastAPI endpoints for financial calculations. It scaffolds the necessary backend code, including input validation, business logic implementation, and API exposure for new programmatic functionalities.

Yes, this skill handles error handling and input validation for Python API routes. It ensures adherence to best practices by automating the creation of Pydantic models alongside the service and route definitions.

You need an existing Zeta Terminal codebase environment to maximize this skill's effectiveness, as it specifically generates new API endpoints following the Zeta Terminal's established architectural patterns and data access layers.

You should avoid using an automated endpoint scaffolder if your backend development task requires breaking the established Router → Service → Repository pattern or implementing custom architectural structures outside the Zeta Terminal system.