Loading ToolBench
A Spring Boot-based MCP server that instantly maps standard Java methods to LLM tool calls using annotations, without boilerplate.
Single tool with minimal definition quality. Tool name 'hello_world' lacks action verb (should be 'greet_user' or similar). Description is adequate (56 chars, within 10-1024 range) but generic. Input schema present with type and description, meeting baseline. No output schema documented. No error handling guidance. No parameter constraints or validation rules. Tool is trivial (demo-only) and lacks production patterns like idempotency, pagination, or recovery guidance.
Returns a greeting to the connecting AI Agent.
Tool name lacks action verb. 'hello_world' does not start with a verb (get_, create_, send_, etc.). Should be 'greet_user' or 'send_greeting' to signal intent to LLM.
No output schema documented. Tool returns a string, but LLMs need explicit schema (type, fields, format) to plan downstream calls and extract data reliably.
No error handling or recovery guidance. Tool lacks documentation of failure modes, error messages, or what the LLM should do if the call fails.
Parameter 'name' lacks format constraints. Description says 'Name of the AI or User' but does not specify length limits, character restrictions, or validation rules.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 43 | 2026-07-28+ | v2 |
Tool is demo-only with no production patterns. No idempotency hint, no destructive/readonly classification, no rate-limit guidance, no audit trail support.