Generate UV Unwrap for a 3D Model

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Adds substantial context beyond the annotations: a stated cost (5 credits), hard input limits with the rejection behavior and the required recovery step, and a precise description of the output transformation (geometry preserved, quads/n-gons triangulated, fresh UVs, grey placeholder material). The annotations only cover generic safety/idempotency hints, so this operational detail is genuinely additive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two tight paragraphs, front-loaded with purpose, then cost, then constraints and output behavior. Every clause carries information (limits, credits, transformation result) and nothing is repeated from the schema or title.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a generation tool with an output schema, the description covers everything an agent needs to invoke it correctly: required input format, size ceiling with the fallback path, cost, and the shape of the returned asset. Return-value details can safely be deferred to the output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so all three parameters (including the model_url vs input_task_id precedence and the response_format enum) are already documented in the schema. The description only reinforces the GLB-only constraint and the 'convert other formats first' step, adding marginal meaning beyond structured data. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ('Make a clean, non-overlapping UV layout') and immediately clarifies the artifact produced (a 'UV white model' for texturing). It is easily distinguished from siblings like meshy_retexture, meshy_remesh, or meshy_convert without opening any schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives clear prerequisites (GLB input only, ≤40,000 faces) and a routing hint for the failure case ('denser meshes are rejected: remesh first'), which points at the meshy_remesh sibling. It positions the tool in the pipeline ('before texturing in Blender, Substance Painter or Unreal'), but never explicitly states when-not to use it or names alternatives beyond the remesh hint.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.