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import_generated_asset

Import 3D assets generated by Hyper3D Rodin into Blender scenes using task UUIDs or request IDs from completed generation tasks.

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 primary handler function for the 'import_generated_asset' tool. It is decorated with @mcp.tool() for registration and @telemetry_tool for telemetry. The function constructs parameters and sends an 'import_generated_asset' command to the Blender addon via the socket connection, handling the core logic of importing the generated asset.
    @telemetry_tool("import_generated_asset")
    @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)}"
  • The decorators @telemetry_tool("import_generated_asset") and @mcp.tool() register the tool with the MCP server and enable telemetry tracking.
    @telemetry_tool("import_generated_asset")
    @mcp.tool()
  • The function signature and docstring define the input schema (parameters: name (str), task_uuid (str optional), request_id (str optional)) and output (result dict or error string).
    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.
        """
Behavior3/5

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

No annotations are provided, so the description carries full burden. It discloses the tool imports assets and returns success status, but lacks details on permissions, error handling, or side effects. It adds some context about modes but doesn't fully compensate for missing annotation coverage.

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?

Front-loaded with the main purpose, followed by parameter explanations and a usage rule. Sentences are efficient, though the parameter list could be integrated more smoothly. Overall, it's appropriately sized with minimal waste.

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?

No annotations or output schema exist, and the description covers parameter semantics well but lacks behavioral details like error cases or return format. Given the complexity (3 parameters, no structured guidance), it's adequate but has clear gaps in completeness.

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?

Schema description coverage is 0%, so the description must compensate. It explains the purpose of each parameter (name for object in scene, task_uuid for MAIN_SITE mode, request_id for FAL_AI mode) and the exclusive choice rule, adding significant value 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 verb 'Import' and the resource 'asset generated by Hyper3D Rodin', specifying it's for assets after generation tasks. It distinguishes from sibling 'import_generated_asset_hunyuan' by specifying Hyper3D Rodin, though not explicitly contrasting them.

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 context: use after generation tasks are completed, and specifies parameter selection based on Hyper3D Rodin Mode (MAIN_SITE vs FAL_AI). However, it doesn't explicitly state when NOT to use it or compare with alternatives like 'import_generated_asset_hunyuan'.

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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