generate_hyper3d_model_via_images

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

There are no annotations, so the description carries the full burden of behavioral disclosure. It only restates the generation action and provides no information about whether the operation is asynchronous, whether it returns a job ID, whether polling is required, or what side effects or prerequisites exist. This leaves important behavior opaque.

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 a single short sentence with no filler, front-loading the action and input type. Every word earns its place; the brevity is a structural strength even though the content is thin.

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 generation tool with no annotations, no output schema, and three optional-looking parameters, the description is incomplete. It does not explain that at least one image source is likely needed, does not indicate that generated assets may require polling or import via sibling tools, and gives no sense of the expected flow or return value.

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 100%, so the baseline is 3. The description itself adds no parameter-level meaning beyond the generic word 'images', and it does not clarify the relationship between input_image_urls and input_image_paths, whether at least one is required, or how bbox_condition affects generation.

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 identifies the verb ('Generate'), the resource ('3D asset using Hyper3D'), and the input medium ('from images'). It is understandable and differentiates from the sibling text-based generation tool by explicitly stating images as the source, though it is still very close to the tool name with little added specificity.

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 phrase 'from images' implies this tool should be used when image-based input is available, which is a minimal usage signal. However, it does not explicitly contrast with generate_hyper3d_model_via_text, does not state prerequisites, and gives no guidance on when not to use it.

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