generate_3d_from_images

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

No annotations are provided, so the description carries the full burden. It discloses input types and output format, but omits critical behavioral details such as whether this is an asynchronous task, whether it returns a job ID or the .glb directly, and how it interacts with get_meshy_task_status. This is a significant gap for a generation tool.

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?

One compact arrow-syntax sentence front-loads the purpose and communicates input constraints, output format, and quality expectation with no filler. Every phrase earns its place.

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 tool with 6 parameters, no output schema, and no annotations, this description is too thin. It does not explain the remaining parameters, the return contract, or asynchronous behavior, and it does not situate the tool within the surrounding workflow of status checking and downstream video/youtube steps.

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 0%, and the description only adds meaning for the images parameter by specifying URL/path formats and a count range. The other five parameters (timeout, enable_pbr, should_remesh, should_texture, texture_prompt) are left entirely to their property names, with no explanation of effect or trade-offs.

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 function: converting 1-4 reference images of one subject into a textured .glb model. The 'Multi-image' qualifier and image-count range distinguish it from the sibling single-image tool. Format of output is explicit.

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?

Provides clear context that the tool accepts 1-4 images of one subject, which implies the multi-image use case. However, it does not explicitly name alternatives like generate_3d_from_image or state when one should be preferred over the other, leaving some routing up to inference.

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