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generate_hunyuan3d_model

Create 3D models from text descriptions or image references and import them into Blender with built-in materials.

Instructions

Generate 3D asset using Hunyuan3D by providing either text description, image reference, 
or both for the desired asset, and import the asset into Blender.
The 3D asset has built-in materials.

Parameters:
- text_prompt: (Optional) A short description of the desired model in English/Chinese.
- input_image_url: (Optional) The local or remote url of the input image. Accepts None if only using text prompt.

Returns: 
- When successful, returns a JSON with job_id (format: "job_xxx") indicating the task is in progress
- When the job completes, the status will change to "DONE" indicating the model has been imported
- Returns error message if the operation fails

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
text_promptNo
user_promptNo
input_image_urlNo
Behavior3/5

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

No annotations are provided, so the description must carry the behavioral burden. It discloses async operation (job_id returned, status changes to DONE), import into Blender, built-in materials, and error returns. However, it omits rate limits, auth requirements, and explicit confirmation of mutation vs read. The coverage is moderate.

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

Conciseness3/5

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

The description is relatively concise but includes parameter descriptions that partially overlap with schema info. The structure is clear: purpose, params, returns. Some details could be more streamlined.

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

Completeness3/5

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

Given the complexity of 3D generation and sibling tools like get_hunyuan3d_status, the description covers async behavior but fails to reference how to track progress or handle failures. It also lacks an output schema. It is adequate but not fully complete.

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

Parameters2/5

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

Schema coverage is 0%, so description must add meaning. It covers text_prompt and input_image_url adequately but completely omits the user_prompt parameter that appears in the schema. This leaves a parameter undocumented, which is a significant gap.

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

Purpose5/5

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

The description clearly states it generates a 3D asset using Hunyuan3D from text or image input and imports into Blender. This distinguishes it from siblings like download_polyhaven_asset (downloads existing assets) and generate_hyper3d_model_via_text (different service), providing a specific verb and resource.

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

Usage Guidelines3/5

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

The description explains when to use (text, image, or both) but lacks explicit guidance on when not to use this tool vs alternatives like generate_hyper3d_model_via_text. No comparisons or prerequisites are mentioned, making it adequate but not exemplary.

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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