generate_hyper3d_model_via_images

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds valuable context: the asset has built-in materials, the model is normalized and may need re-scaling, and it returns a success/failure message. It doesn't disclose potential side effects (e.g., whether it replaces existing objects or requires a specific scene state) or whether the operation is asynchronous, but the disclosed behavior goes beyond generic statements.

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 well-structured with a purpose statement, behavioral notes, and a parameter list. It front-loads the primary purpose. Some redundancy exists ('Even if only one image is provided, wrap it into a list' appears twice), which is slightly wasteful but not harmful. Overall, it's compact and informative.

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?

The description thoroughly covers parameters and the result message, but it omits important operational context such as whether generation is synchronous or requires polling (given the sibling tool poll_rodin_job_status), and any prerequisites or side effects on the Blender scene. The output schema exists, so return values are partially covered, but the async behavior gap is significant for correct tool usage.

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 the description fully compensates. It explains each parameter in detail: absolute paths for input_image_paths, URLs for input_image_urls, wrapping single images in lists, mode-specific requirements, and bbox_condition's list-of-ints format and purpose (ratio control). It also clarifies mutual exclusivity, something the schema alone doesn't convey.

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 tool's function: 'Generate 3D asset using Hyper3D by giving images of the wanted asset, and import the generated asset into Blender.' It specifies the method (images), the tool (Hyper3D), and the outcome (import into Blender). This distinguishes it from the sibling tool generate_hyper3d_model_via_text, which uses text input.

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 provides clear context for when to use the tool: when you have images of an asset to generate a 3D model. It also gives explicit mode-dependent guidance on which parameter to use (input_image_paths vs input_image_urls) and notes that only one should be provided. However, it doesn't explicitly mention alternatives or exclusions (e.g., 'use via_text when you have text'), leaving some room for ambiguity.

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