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 key behavioral traits: the asset has built-in materials, normalized size requiring potential re-scaling, and returns a success/failure message. However, it misses details like permissions needed, rate limits, whether generation is synchronous/asynchronous, or error handling specifics, which are important for a generative tool.

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 well-structured with a clear opening sentence, followed by key details and a parameter section. Every sentence adds value: the first states the core action, the second notes built-in materials, the third advises on scaling, and the parameter explanations are necessary. It's front-loaded and avoids redundancy, though it could be slightly more concise by integrating parameter info more seamlessly.

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 no annotations and no output schema, the description provides basic context: purpose, key behaviors, and parameter semantics. However, for a generative tool with 2 parameters and complex output (3D asset import), it lacks details on output format beyond success/failure message, error conditions, or integration specifics with Blender. This leaves gaps for an agent to operate effectively in a multi-tool environment.

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 must compensate. It adds meaningful semantics: 'text_prompt' is described as 'A short description of the desired model in **English**,' and 'bbox_condition' as 'Optional... Controls the ratio between [Length, Width, Height] of the model.' This clarifies purpose and constraints beyond the bare schema, though it could specify format details like units for bbox_condition.

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 purpose: 'Generate 3D asset using Hyper3D by giving description of the desired asset, and import the asset into Blender.' It specifies the verb (generate), resource (3D asset), technology (Hyper3D), and destination (Blender). However, it doesn't explicitly differentiate from siblings like 'generate_hunyuan3d_model' or 'generate_hyper3d_model_via_images' beyond the 'via_text' distinction in the name.

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 context through phrases like 'by giving description' and mentions re-scaling after generation, but it lacks explicit guidance on when to use this tool versus alternatives. For example, it doesn't compare with 'generate_hyper3d_model_via_images' or other 3D generation tools in the sibling list, leaving the agent to infer based on the 'via_text' aspect.

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