@autobe/agent
Version:
AI backend server code generator
115 lines (108 loc) • 4.04 kB
text/typescript
export interface IAutoBeTestAuthorizationWriteApplication {
/**
* Main entry point for AI Function Call - generates authorization utility
* functions.
*
* The AI executes this function to generate authorization functions that
* handle authentication flows (login, join, refresh, etc.) for different
* actor types. This structured approach ensures consistent authentication
* handling across the test suite.
*
* @param props Complete specification for authorization function generation
*/
write(props: IAutoBeTestAuthorizationWriteApplication.IProps): void;
}
export namespace IAutoBeTestAuthorizationWriteApplication {
export interface IProps {
/**
* Step 1: Strategic authorization analysis.
*
* AI analyzes the operation to understand authorization requirements,
* including the type of authentication flow, actor permissions, and
* required SDK functions. This analysis forms the foundation for generating
* appropriate authorization utilities.
*
* Workflow: Operation analysis → Authorization strategy → Implementation
* plan
*/
think: string;
/**
* Step 2: Actor identification.
*
* AI determines the actor (user type) for this authorization function. This
* should be extracted from the context, such as the API path or operation
* details.
*
* Examples: "user", "admin", "moderator", "seller", "customer"
*/
actor: string;
/**
* Step 4: Initial authorization function implementation.
*
* AI generates the authorization utility function that properly handles the
* authentication flow. The implementation must use correct SDK functions,
* return required authentication data, and include comprehensive error
* handling with fallback logic where needed.
*
* Critical: NO import statements, start directly with 'export async
* function'
*/
draft: string;
/**
* Steps 5-6: Code review and final refinement process.
*
* Contains the iterative improvement workflow that transforms the initial
* draft into production-ready authorization code. The review phase
* identifies issues to fix, followed by the final phase that produces the
* polished implementation ready for use in test scenarios.
*
* Workflow: Draft → Review analysis → Final implementation
*/
revise: IReviseProps;
}
export interface IReviseProps {
/**
* Step 5: Code review and quality assessment.
*
* AI performs a thorough review of the draft implementation, checking for:
*
* **Technical Correctness:**
*
* - Proper SDK function usage and parameter types
* - Appropriate return types and data structures
* - TypeScript compilation compatibility
*
* **Authorization Logic:**
*
* - Proper handling of authentication flows
* - Correct token/session management
* - Appropriate error handling and fallback strategies
* - Security best practices
*
* **Code Quality:**
*
* - Clear variable naming and code organization
* - Comprehensive error messages
* - Proper async/await usage
* - Type safety without any/unknown usage
*
* The review must provide specific, actionable feedback for improvements.
*/
review: string;
/**
* Step 6: Final production-ready authorization function.
*
* AI produces the final version incorporating all review feedback. This
* represents the completed authorization utility ready for use in test
* scenarios. When the draft is already perfect with no issues found during
* review, this value can be null.
*
* All identified issues must be resolved, and the code must meet production
* quality standards for test utilities.
*
* Workflow: Review feedback → Apply improvements → Production-ready code
* (or null if no changes needed)
*/
final: string | null;
}
}