Loading ToolBench
The server has 3 tools with basic descriptions and input schemas, but quality is inconsistent. Tool naming is reasonably clear (verb-starting), but descriptions lack depth on usage context and error cases. Schemas are present but sparse, parameters have types and basic descriptions, but lack constraints, ranges, and error guidance. Output schemas are not documented. The virtual_tryon tool is the most complete, but base64_to_url and test_connection are minimal. Parameter descriptions are generic (e.g. 'URL of the model/person image' without format guidance). No error recovery guidance. Overall: mediocre, below production baseline of 70+.
Convert a base64 encoded image to a data URI that can be used with Replicate.
Test the connection to Replicate API without running a model.
Apply virtual try-on to put a garment on a model using Replicate API.
test_connection has minimal description (11 words, <60 chars), does not explain when/why to use it or what success/failure means
No output schemas documented for any tool. LLMs cannot predict response structure or plan downstream calls. base64_to_url returns dict{success, url, ...}, test_connection returns dict{...}, virtual_tryon returns dict{...}, all undocumented.
Parameters lack format constraints and ranges. 'model_image' and 'garment_image' accept URLs but no validation of format (must be HTTP(S), not just any string). 'seed' accepts integer but no range (1-2^31?). 'num_inference_steps' accepts 1-any, but Replicate likely has limits (e.g. 1 - 150).
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-22 | D | 50 | 2026-07-28+ | v2 |
| 2026-03-09 | D | 55 | - | v1 |
No error recovery guidance. base64_to_url returns {success: false, error: '...', message: '...'} but does not tell LLM what to do next (retry? ask user? call different tool?). Errors are not categorized as retryable vs fatal.
Parameter descriptions are generic and lack actionable detail. 'Custom prompt for generation (optional)' does not explain expected format, length, or role of prompt in the model. 'Mask expansion ratio (default: 0.025)' lacks range/unit context.
No destructive operation warnings. virtual_tryon calls Replicate API (write operation, potentially billable) but description does not mention cost, rate limits, or that this will consume credits/incur charges.
base64_to_url's 'image_type' parameter defaults to 'png' and accepts only {png, jpg, jpeg, gif, webp}, but this is not declared as an enum in the schema. Free-form string invites invalid values (e.g. 'JPEG', 'tiff').