generate_hyper3d_model_via_text

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

With no annotations provided, the description must fully disclose behavior. It mentions built-in materials, normalized size, and a success/failure return message. Missing critical context: the tool likely starts an async generation job (siblings like poll_rodin_job_status and get_hyper3d_status imply async), no mention of job polling status, blocking behavior, or side effects on the Blender scene.

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, with main purpose stated first, followed by bullet-like details. It contains no filler. Could benefit from structured formatting (e.g., explicit parameter descriptions separately) for easier parsing, but overall efficient.

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?

Given the complexity (generative model, import into Blender, multiple sibling tools), the description lacks essential context: async nature, how to poll/retrieve results, status checking, failure handling details, import behavior (e.g., replaces existing objects?), and any prerequisites (Blender open?). No output schema, so return format is vague. Incomplete for a generative tool.

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 explain parameters. It explains text_prompt (short English description) and bbox_condition (list of 3 floats for L/W/H ratio). However, user_prompt is completely omitted. bbox_condition explanation is helpful but could be more precise (e.g., 'array of three numbers' instead of 'list of floats of length 3').

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 'generate 3D asset using Hyper3D by giving description' and 'import the asset into Blender.' It uses specific verb-resource and distinguishes from sibling tools like generate_hyper3d_model_via_images (different input modality) and download/import tools (different origin).

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 advises providing a short description in English and notes that re-scaling may be useful due to normalized size. However, it does not specify when to prefer this tool over alternatives (e.g., generate_hunyuan3d_model or generate_hyper3d_model_via_images) and lacks exclusion criteria or prerequisites.

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