Analysis of the requirements structure and domain organization.
Documents the agent's understanding of the business requirements, including what major business domains were identified, how these domains relate to each other, what organizational patterns exist in the requirements, and what foundational vs domain-specific components are needed.
Timestamp when the event was created.
ISO 8601 formatted date-time string indicating when this event was emitted by the system. This timestamp is crucial for event ordering, performance analysis, and debugging the agent workflow execution timeline.
Format: "YYYY-MM-DDTHH:mm:ss.sssZ" (e.g., "2024-01-15T14:30:45.123Z")
Array of database component groups organized by business domain.
Each group represents a logical partition of the database based on business requirements and domain analysis. Groups are mutually exclusive (no component appears in multiple groups) and collectively exhaustive (all components are covered). The array typically contains 2-10 groups depending on the project scale and domain complexity.
These groups will be used by subsequent Database agent invocations to extract components for specific subsets of the application.
A unique identifier for the event.
Function calling trial statistics for the operation.
Records the complete trial history of function calling attempts, tracking total executions, successful completions, consent requests, validation failures, and invalid JSON responses. These metrics reveal the reliability and quality of AI agent autonomous operation with tool usage.
Trial statistics are critical for identifying operations where agents struggle with tool interfaces, generate invalid outputs, or require multiple correction attempts through self-healing spiral loops. High failure rates indicate opportunities for system prompt optimization or tool interface improvements.
Rationale for the component grouping decisions.
Explains why the groups were organized this way, including why each component group was created, why certain domains were combined or kept separate, how the grouping reflects the business domain structure, and what considerations drove the component ordering.
Iteration number of the requirements analysis this grouping reflects.
Indicates which version of the requirements analysis this group organization is based on. This step number ensures that the database grouping remains synchronized with evolving requirements throughout the development lifecycle.
The step value enables proper tracking of how database organization evolves as the project requirements are refined through iterations.
Detailed token usage metrics for the operation.
Contains comprehensive token consumption data including total usage, input token breakdown with cache hit rates, and output token categorization by generation type (reasoning, predictions). This component-level tracking enables precise cost analysis and identification of operations that benefit most from prompt caching or require optimization.
Token usage directly translates to operational costs, making this metric essential for understanding the financial implications of different operation types and guiding resource allocation decisions.
Unique identifier for the event type.
A literal string that discriminates between different event types in the AutoBE system. This field enables TypeScript's discriminated union feature, allowing type-safe event handling through switch statements or conditional checks.
Examples: "analyzeWrite", "databaseSchema", "interfaceOperation", "testScenario"
Event fired when the Database agent generates logical groups for organizing database component extraction.
This event occurs specifically in large-scale projects where the volume of business requirements necessitates dividing database component generation into manageable chunks. The Database agent analyzes the requirements and creates organizational groups that partition the component extraction work based on business domains and functional areas.
The groups generated in this event serve as the foundation for subsequent component extraction cycles, ensuring that:
This grouping phase is critical for maintaining scalability and consistency in projects with extensive business requirements and complex domain models.
Author
Samchon