EU AI Act compliance chatbot using hybrid retrieval with vector similarity search and knowledge graph lookups
Two tools present with minimal quality. 'chat' has a basic description and single input parameter with type and description, but lacks output schema documentation. 'health' is a trivial health check with no parameters and minimal description. Neither tool has error handling guidance, recovery hints, or actionable error messages. No tool annotations (readOnlyHint, destructiveHint, idempotentHint). Descriptions are present but generic. No pagination, no structured output schema, no composition patterns. The server exposes internal component state in error responses rather than user-friendly guidance.
Receives a user query, performs hybrid retrieval, and generates an answer.
Basic health check endpoint.
No output schema documented for 'chat' tool. LLMs cannot plan downstream operations or extract structured data. ChatResponse model exists in code but is not exposed in tool definition.
Error responses expose internal component state ('Initialization failed', 'Retriever not initialized') instead of actionable recovery guidance. LLM cannot determine next steps.
'health' tool is trivial and provides no value to an agent. A basic health check endpoint does not warrant a tool definition, it should be implicit in server availability.
No tool annotations present. 'chat' and 'health' should declare readOnlyHint=true to signal they are safe to retry and do not modify state.
Inferred effective spec: <=2025-11-25.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 46 | <=2025-11-25 | v2 |
'chat' tool accepts free-form query string with no constraints, format hints, or length limits. LLM may pass extremely long or malformed queries without guidance.