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download_sketchfab_model

Download and import a Sketchfab model via UID, with automatic scaling to a specified target size in Blender units.

Instructions

Download and import a Sketchfab model by its UID.
The model will be scaled so its largest dimension equals target_size.

Parameters:
- uid: The unique identifier of the Sketchfab model
- target_size: REQUIRED. The target size in Blender units/meters for the largest dimension.
              You must specify the desired size for the model.
              Examples:
              - Chair: target_size=1.0 (1 meter tall)
              - Table: target_size=0.75 (75cm tall)
              - Car: target_size=4.5 (4.5 meters long)
              - Person: target_size=1.7 (1.7 meters tall)
              - Small object (cup, phone): target_size=0.1 to 0.3

Returns a message with import details including object names, dimensions, and bounding box.
The model must be downloadable and you must have proper access rights.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
uidYes
target_sizeYes
user_promptNo
Behavior4/5

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

With no annotations, the description carries the burden. It discloses the scaling behavior ('largest dimension equals target_size'), return value ('message with import details including object names, dimensions, and bounding box'), and prerequisites ('must be downloadable and proper access rights'). It doesn't explicitly describe side effects on the Blender scene, but 'import' implies a create operation, which is acceptable.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose and efficiently explains scaling. The examples for target_size are helpful but slightly verbose. The parameter list omits user_prompt, which is a structural gap, but overall it's well-organized.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the operation, scaling behavior, return format, and access prerequisites. It even gives sizing guidance. The lack of an explanation for user_prompt and no alternative pointers keep it from being a 5.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

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 does a great job on uid and target_size, including examples and units. However, it completely omits the third parameter, user_prompt, which is in the schema. This incomplete coverage prevents a higher score.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with 'Download and import a Sketchfab model by its UID,' which is a specific verb+resource pair. It clearly distinguishes itself from sibling tools like search_sketchfab_models and get_sketchfab_model_preview by focusing on the download/import action and the unique scaling-to-target-size behavior.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It provides clear usage context: requires a UID, target_size, and proper access rights. It doesn't explicitly name alternatives or exclusions, but the context is sufficient for an agent to infer when to use it (when a UID is available and the model is downloadable).

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

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