generate_hyper3d_model_via_images

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

With no annotations, the description takes on the burden of disclosing behavior. It mentions that the asset has built-in materials, that the model has normalized size (which may require re-scaling), and that the tool returns a success/failure message. It also implies the side effect of importing into Blender. This is valuable context beyond the schema, though it could mention asynchronous behavior or potential scene modifications in more detail.

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 purpose statement, behavioral notes, a parameter list, and a return statement. It is somewhat long but each sentence adds relevant information. The parameter details are organized and easy to scan. No redundant text.

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 tool's complexity and lack of an output schema, the description provides a solid overview: purpose, key parameters, behavioral caveats, and return type. The main omission is user_prompt, which is part of the schema but unexplained. Overall, an agent can reasonably understand how to use the tool, though some edge cases (e.g., asynchronous behavior) are not covered.

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?

The description provides detailed semantics for three of the four parameters: input_image_paths (absolute paths, wrap in list, required conditionally), input_image_urls (URLs, wrap in list), and bbox_condition (list of ints length 3, controls ratio). It does not explain user_prompt, which is a gap considering the schema has no descriptions and the description attempts to cover parameters.

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: generating a 3D asset via Hyper3D from images and importing it into Blender. It specifies the input (images) and distinguishes it from sibling tools like generate_hyper3d_model_via_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?

Provides explicit guidance on when to use input_image_paths vs input_image_urls based on the current mode (MAIN_SITE vs FAL_AI). It clearly explains that only one input should be given, which clarifies usage conditions. However, it does not explicitly state when to choose this tool over alternatives like generate_hyper3d_model_via_text.

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