generate_hyper3d_model_via_text

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

With no annotations, the description discloses several behavioral traits: it mentions the built-in materials, the normalized size (suggesting re-scaling may be useful), and that it imports the asset into Blender. It also states the return message indicates success or failure. While it does not cover every possible side effect (e.g., whether the process is asynchronous or long-running), it provides more than basic purpose-only information.

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 well-structured. It starts with a clear purpose, then adds relevant behavioral notes (materials, normalized size), lists parameters with explanations, and ends with return value. No unnecessary repetition or verbose language is present.

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 tool with only two parameters and a simple return, the description covers the key aspects: input, optional parameter, output behavior, and side effects (import). It does not mention any asynchronous behavior or need to poll status, which might be relevant given sibling status tools, but the return message implies synchronous completion. Overall, it is sufficiently complete for an agent to use correctly.

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?

The description explicitly documents both parameters with meaningful details: text_prompt is required, should be in English, and is a short description; bbox_condition is optional, must be a list of three floats, and controls the Length/Width/Height ratio. This significantly adds value over the bare schema, which only provides titles and types. Since schema description coverage is 0%, the description fully compensates.

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 description of the desired asset, and import the asset into Blender.' It specifies the method (text description) and the specific service (Hyper3D), distinguishing it from siblings like generate_hunyuan3d_model and generate_hyper3d_model_via_images. The verb 'generate' and resource '3D asset' are precise and unambiguous.

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 use: 'by giving description of the desired asset' indicates the tool is for text-based generation. It also mentions the optional bbox_condition parameter to control dimensions. However, it does not explicitly mention alternatives (e.g., generate_hyper3d_model_via_images for image-based generation) or state when not to use this tool, so it lacks explicit exclusions.

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