generate_hyper3d_model_via_text

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 does well by disclosing that the tool imports the asset into Blender, that materials are built-in, that the model size is normalized and may need rescaling, and that it returns a success/failure message. It does not mention whether generation is asynchronous, whether it blocks, or how the imported object can be referenced afterward, but it provides substantial useful behavior context.

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 compact and well-structured: purpose and side effect first, then relevant model characteristics, then parameter details, then return value. Every sentence adds information, and there is no redundant restatement of schema fields or filler.

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 two-parameter tool with no annotations and no output schema, the description is nearly complete. It covers input semantics, generated asset characteristics, the Blender import side effect, and the return message. Minor gaps are lack of clarification about asynchronous behavior and how the agent can locate or reference the imported asset after success.

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%, so the description's parameter notes are essential. It explains that text_prompt must be a short English description, and that bbox_condition is optional, must be a list of floats of length 3, and controls the Length/Width/Height ratio. This adds meaningful semantic detail beyond the raw schema, though ranges or a more precise ratio explanation would strengthen it further.

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 states a specific verb ('Generate'), the specific service (Hyper3D), the input mode (description/text), and the side effect (import into Blender). It also adds useful purpose details: built-in materials and normalized size. This clearly distinguishes it from image-based generation like generate_hyper3d_model_via_images, even though that sibling is not named.

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 implies when to use the tool: when you have a textual description of a 3D asset and want it generated and imported into Blender. However, it does not explicitly contrast with generate_hyper3d_model_via_images, import_generated_asset, or the other generation tools. No when-not-to-use guidance or alternative selection criteria are provided.

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