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. It discloses the output (built-in materials), a key property (normalized size), and the return type (success/failure message). However, it does not mention potential side effects like scene modification, generation time, or error handling for invalid prompts. The behavioral disclosures are helpful but not comprehensive.

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 brief and well-organized: a purpose sentence, two short behavioral notes, and a parameter list. Each sentence contributes useful information without redundancy. The parameter bullet points are easy to scan, and the entire description is front-loaded with the core action.

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 covers purpose, key output properties, parameter semantics for two of three params, and the return message. It lacks explanation for the user_prompt parameter and does not mention if the generation process is asynchronous (especially given sibling tools like poll_rodin_job_status). For a generation tool, additional context about workflow expectations (e.g., importing modifies the Blender scene) could be beneficial.

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 is the sole source of parameter meaning. It explains text_prompt (short English description) and bbox_condition (optional list of floats for length/width/height ratio). However, user_prompt from the schema is not described, leaving a parameter unaccounted for. The descriptions provided are clear and add value beyond the bare schema.

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.' This identifies the specific service (Hyper3D), the input modality (text description), and the output action (import into Blender). It distinguishes from sibling tools like generate_hyper3d_model_via_images, which uses images instead of text.

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 usage when a text description is available, but it does not explicitly reference alternatives or exclusionary conditions. The mention of 'text' in the description gives some guidance, yet there is no comparison to generate_hunyuan3d_model or other 3D generation tools. No 'when not to use' scenarios are provided.

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