generate_hyper3d_model_via_images

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

No annotations provided, so description carries full burden. It mentions built-in materials and normalized size (useful for re-scaling) and notes return of success/failure message. But it omits whether the generation is asynchronous (sibling poll_rodin_job_status suggests async), nor does it disclose potential side effects or prerequisites.

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?

The description is concise and front-loaded with purpose. Parameter explanations are clear but could be more structured (e.g., bullet points). The length is appropriate.

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?

Missing output schema, and description only says 'Returns a message indicating success or failure'—no detail on the actual generated asset (e.g., how to access it). Also lacks context on prerequisites (Hyper3D addon, Blender running) and relationship to polling tools.

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 coverage is 0%, so description must detail parameters. It explains input_image_paths (absolute paths, wrap in list), input_image_urls (URLs, wrap in list), and bbox_condition (optional list of ints length 3 for ratio). This adds significant value beyond the schema.

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 clearly states the purpose: generating a 3D asset using Hyper3D from images and importing into Blender. It distinguishes from siblings like generate_hyper3d_model_via_text (text input) and generate_hunyuan3d_model (different generator).

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?

The description explains that only one of input_image_paths or input_image_urls should be given based on mode, and provides conditions for each. However, it lacks explicit guidance on when to prefer this tool over alternatives like generate_3d_from_image.

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