generate_hyper3d_model_via_images

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

With no annotations, the description must fully disclose behavior. It mentions built-in materials, normalized size, and the need for re-scaling, but omits important traits: whether the tool modifies existing assets, required permissions, or side effects. The return is only described as a 'success or failure' message, lacking detail on what the generated asset reference is.

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 reasonably concise, with the main purpose stated upfront. It covers key points in a few sentences. However, some information (e.g., the return message) could be condensed without loss of clarity.

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 that an output schema exists (not shown), the description does not need to detail return values, but it only says 'message indicating success or failure,' which is vague. It misses details on error conditions, prerequisites (e.g., Blender must be running), and integration with sibling tools like import_generated_asset. Overall, it covers the basics but leaves gaps for a complex generation 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 the description must compensate. It clearly explains that input_image_paths require absolute paths and both must be lists even for single images, and that bbox_condition controls length/width/height ratio with a list of three ints. This adds substantial meaning beyond the schema's bare type definitions.

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 generates a 3D asset from images using Hyper3D and imports it into Blender. It distinguishes itself from siblings like generate_hyper3d_model_via_text by specifying image input. Additional details (built-in materials, normalized size) clarify the exact output.

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 explains that only one of input_image_paths or input_image_urls should be used based on the current mode (MAIN_SITE vs FAL_AI). This provides context for parameter selection. However, it does not explicitly compare to alternatives (e.g., when to use text-based generation) or state when not to use this tool.

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