Loading ToolBench
A Model Context Protocol server that bridges AI providers to IDEs via MCP-ready configurations. Manages multiple agents, handles text generation requests, and provides usage tracking and cost management.
Single tool 'generate_text' has a basic schema and description, but critical gaps prevent production use. Description is adequate (95 chars, within 10-1024 range) but lacks WHEN to use it, prerequisites, or state-modification warnings. Input schema is present with proper type and required field, but parameter 'prompt' has NO description, violating the rule that every parameter needs one. No output schema documented. No error handling guidance. Tool does not follow verb_noun pattern clearly (generate_text is acceptable but generic). No pagination, no structured output guidance, no recovery hints for failures.
Generate text using the agent's configured provider and model. Use this for ALL text generation tasks.
Parameter 'prompt' lacks description. LLMs cannot infer what format, length, or content is expected.
No output schema documented. LLMs do not know what fields to expect in the response or how to chain downstream calls.
Tool description does not state that it modifies state (generates/produces text) or when to use it vs. other tools. Missing WHEN and WHY context.
Error handling returns JSON error objects but provides no recovery guidance. LLMs cannot determine if errors are retryable or what to do next.
No input validation constraints documented (e.g., max prompt length, required format). Unbounded string invites LLM to pass absurdly long prompts.
Inferred effective spec: <=2025-11-25.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | D | 50 | <=2025-11-25 | v2 |