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generate_3d_from_image

Generate a textured 3D model from a photo or render. Provide an image URL or local path to receive a .glb file and task ID.

Instructions

Image-to-3D: a photo/render (public URL or local file path) -> textured .glb. Returns the local .glb path and the Meshy task id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
imageYes
texture_promptNo
enable_pbrNo
should_textureNo
should_remeshNo
timeoutNo
Behavior2/5

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

With no annotations provided, the description must disclose all behavioral traits. It only mentions the input/output format and returns a task ID, but does not explain side effects, async nature, permission requirements, or the effect of parameters like 'should_texture', 'enable_pbr', or 'timeout'. This leaves significant behavioral gaps.

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

Conciseness4/5

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

The description is very concise (one short sentence) and front-loads the core purpose. No unnecessary words, but could be restructured to include key parameter details without losing brevity.

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

Completeness1/5

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

Given the tool has 6 parameters, no output schema, and no annotations, the description is severely incomplete. It does not explain the processing flow, return value structure, parameter dependencies, or error handling. The agent would have little context to use the tool correctly.

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

Parameters1/5

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

Schema description coverage is 0%, and the description adds no explanation for any of the 6 parameters. It only mentions the 'image' input implicitly, but does not describe 'texture_prompt', 'enable_pbr', 'should_texture', 'should_remesh', or 'timeout'. This fails to help an agent understand parameter semantics.

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

Purpose4/5

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

The description clearly states the tool converts a photo/render (single image) to a textured .glb file, and mentions output format. It implicitly distinguishes from sibling 'generate_3d_from_images' by specifying singular input. However, it could be more explicit about the tool's specific role among many 3D generation tools.

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

Usage Guidelines2/5

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

The description does not provide any guidance on when to use this tool versus alternatives like 'generate_3d_model' or 'retexture_model'. It only implies usage for single-image input, but lacks explicit context or exclusion criteria.

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

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