Generate 3D GLB models from front, back, left, and right reference images by starting a durable Hunyuan3D-2mv job with prompt, quality, and texture options.
Start a durable Hunyuan3D-2mv job from named canonical views.
| Name | Required | Description | Default |
|---|---|---|---|
| seed | No | ||
| prompt | Yes | ||
| quality | No | standard | |
| material_hints | No | ||
| back_image_path | No | ||
| left_image_path | No | ||
| front_image_path | Yes | ||
| generate_texture | No | ||
| right_image_path | No |
Changes observed during successful MCP inspections.
v0.4.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations at all, the description carries the full behavioral burden and falls well short. It does not state that the job is asynchronous, whether a job identifier is returned for later status/artifact retrieval, what happens if only the front view is supplied, whether generation is costly or rate-limited, or whether the operation can be cancelled.
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?
A single front-loaded sentence with no filler or redundancy. It is efficient, though its brevity is under-specification rather than disciplined conciseness given the tool's complexity.
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 nine-parameter generative job tool with no annotations and no output schema, the description is far too thin. An agent cannot tell what the call returns, how to track completion, or how the optional view paths and quality settings interact, all of which the description would need to supply.
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 there are nine parameters, so the description must compensate and largely does not. 'Named canonical views' gives some hint that the image path parameters are per-view, but prompt, seed, quality, material_hints, and generate_texture receive no meaning at all, including how the quality enum affects the job.
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?
The description gives a specific verb ('Start') and resource ('Hunyuan3D-2mv job') and scopes it to multiview input from 'named canonical views', which maps onto the front/back/left/right image parameters. It distinguishes itself from job-control siblings like get_generation_status or cancel_generation, though it does not differentiate itself from create_generation_batch.
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?
There is no explicit when-to-use guidance, no prerequisites, and no named alternative. The word 'durable' faintly implies an async job that must later be polled, but the agent is left to infer that from sibling names rather than from the description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.