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import_generated_asset

Import 3D assets generated by Hyper3D Rodin into Blender scenes using task UUID or request ID parameters for AI-assisted modeling workflows.

Instructions

Import the asset generated by Hyper3D Rodin after the generation task is completed.

Parameters:

  • name: The name of the object in scene

  • task_uuid: For Hyper3D Rodin mode MAIN_SITE: The task_uuid given in the generate model step.

  • request_id: For Hyper3D Rodin mode FAL_AI: The request_id given in the generate model step.

Only give one of {task_uuid, request_id} based on the Hyper3D Rodin Mode! Return if the asset has been imported successfully.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
task_uuidNo
request_idNo

Implementation Reference

  • The @mcp.tool() decorated function that implements the import_generated_asset tool. It constructs parameters and sends an 'import_generated_asset' command to the Blender addon via socket connection. Includes input schema in the docstring parameters.
    @mcp.tool()
    def import_generated_asset(
        ctx: Context,
        name: str,
        task_uuid: str=None,
        request_id: str=None,
    ):
        """
        Import the asset generated by Hyper3D Rodin after the generation task is completed.
    
        Parameters:
        - name: The name of the object in scene
        - task_uuid: For Hyper3D Rodin mode MAIN_SITE: The task_uuid given in the generate model step.
        - request_id: For Hyper3D Rodin mode FAL_AI: The request_id given in the generate model step.
    
        Only give one of {task_uuid, request_id} based on the Hyper3D Rodin Mode!
        Return if the asset has been imported successfully.
        """
        try:
            blender = get_blender_connection()
            kwargs = {
                "name": name
            }
            if task_uuid:
                kwargs["task_uuid"] = task_uuid
            elif request_id:
                kwargs["request_id"] = request_id
            result = blender.send_command("import_generated_asset", kwargs)
            return result
        except Exception as e:
            logger.error(f"Error generating Hyper3D task: {str(e)}")
            return f"Error generating Hyper3D task: {str(e)}"
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions that the tool imports an asset and returns success status, but lacks details on behavioral traits such as required permissions, error handling, rate limits, or what 'import' entails (e.g., file format, storage location). For a tool with no annotations, this leaves significant gaps in understanding its operation.

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 well-structured and appropriately sized, with a clear opening sentence stating the purpose, followed by parameter details and usage rules. Every sentence adds value, such as explaining parameter dependencies and the return statement. It could be slightly more concise by integrating the return information into the first sentence, but overall it's efficient.

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

Completeness3/5

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

Given the complexity (3 parameters, no annotations, no output schema), the description covers the basics: purpose, parameters, and return indication. However, it lacks details on what 'import' involves (e.g., asset format, integration into a scene), error conditions, or output specifics beyond success status. This makes it adequate but incomplete for a tool with no structured support.

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

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description must compensate, and it does so effectively. It explains the purpose of all three parameters: 'name' as the object name in scene, 'task_uuid' for MAIN_SITE mode, and 'request_id' for FAL_AI mode. It also clarifies the exclusive choice between task_uuid and request_id, adding crucial semantic context beyond the bare schema.

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

Purpose4/5

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

The description clearly states the action ('Import') and resource ('asset generated by Hyper3D Rodin after the generation task is completed'), making the purpose understandable. However, it doesn't explicitly distinguish this tool from sibling tools like 'download_polyhaven_asset' or 'download_sketchfab_model', which also import assets but from different sources.

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?

The description provides clear context on when to use this tool: after a Hyper3D Rodin generation task is completed. It also specifies that parameters depend on the Hyper3D Rodin mode (MAIN_SITE vs. FAL_AI), offering guidance on parameter selection. However, it doesn't mention when not to use it or explicitly compare it to alternatives like other asset import tools.

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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