Summary of preliminary data acquired by the agent during RAG.
Contains lightweight identifiers for each kind of preliminary data that was
loaded into the agent's local context before producing its output. Only the
kinds specified by the Kind type parameter are present.
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")
The reviewed groups with all revisions applied.
Contains the complete list of component group skeletons after review, with all revisions applied. Groups that were added, removed, or modified are reflected in this final group structure used for subsequent authorization and component table generation.
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.
Comprehensive review analysis of the group organization.
Contains the AI agent's detailed evaluation of the group structure including validation of domain completeness, group boundaries, naming conventions, and kind assignments.
Review Dimensions:
Array of group revision operations applied during the review.
Contains all create, update, and erase operations that were identified and applied during the review process. Each operation includes a reason explaining why the change was necessary.
Iteration number of the requirements analysis this group review was performed for.
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 reviews and validates the component group organization during the database design process.
This event occurs after the initial group generation phase, where the Database Group agent has organized business domains into logical component groups. The review validates the group organization against business requirements, checks for missing or redundant groups, verifies domain boundaries, and ensures proper kind assignment.
The review process ensures that the group structure provides a solid foundation for subsequent component and authorization table generation by identifying and correcting organizational issues before table extraction begins.
Author
Michael