Loading ToolBench
An MQTT-based agent-to-agent communication framework using Pydantic for protocol definitions and paho-mqtt for MQTT transport
Single tool 'echo_message' has a minimal description (28 chars, below 20-char floor) and lacks a complete, visible input schema in the source. The tool is registered via Python function introspection in agent.py, but no explicit JSON Schema is defined or exposed. Parameter 'message' has a type hint (str) in the function signature but no description in the schema. No output schema is documented. Error handling is minimal, the agent catches exceptions but does not guide recovery. The tool does one thing (echo), but the definition quality is severely hampered by missing schema documentation and inadequate descriptions.
Echoes back the received message.
No explicit input schema visible. Tool definition inferred from Python function signature only; no JSON Schema with type and description for 'message' parameter.
Tool description is 28 characters ('Echoes back the received message.'), below the 20-char floor for scoring. Lacks context on WHEN to use, WHAT it returns, and any prerequisites.
No output schema documented. LLM cannot infer what fields or structure the tool returns, breaking downstream tool chaining.
Parameter 'message' lacks a description in the schema. LLM cannot determine expected format, constraints, or purpose beyond the name.
Error handling in handle_task() catches exceptions but returns raw error strings without recovery guidance or error classification (retryable vs. fatal).
Inferred effective spec: <=2025-11-25.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 28 | <=2025-11-25 | v2 |