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poll_rodin_job_status

Monitor Hyper3D Rodin generation task completion status in Blender. Check if 3D model generation is finished, in progress, or failed using subscription key or request ID.

Instructions

Check if the Hyper3D Rodin generation task is completed.

For Hyper3D Rodin mode MAIN_SITE: Parameters: - subscription_key: The subscription_key given in the generate model step.

Returns a list of status. The task is done if all status are "Done".
If "Failed" showed up, the generating process failed.
This is a polling API, so only proceed if the status are finally determined ("Done" or "Canceled").

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

Returns the generation task status. The task is done if status is "COMPLETED".
The task is in progress if status is "IN_PROGRESS".
If status other than "COMPLETED", "IN_PROGRESS", "IN_QUEUE" showed up, the generating process might be failed.
This is a polling API, so only proceed if the status are finally determined ("COMPLETED" or some failed state).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
subscription_keyNo
request_idNo

Implementation Reference

  • The handler function for the 'poll_rodin_job_status' tool, decorated with @mcp.tool() for registration and @telemetry_tool for telemetry. It polls the Hyper3D Rodin job status by sending a command to the Blender addon via socket connection, handling either subscription_key or request_id parameters.
    @telemetry_tool("poll_rodin_job_status")
    @mcp.tool()
    def poll_rodin_job_status(
        ctx: Context,
        subscription_key: str=None,
        request_id: str=None,
    ):
        """
        Check if the Hyper3D Rodin generation task is completed.
    
        For Hyper3D Rodin mode MAIN_SITE:
            Parameters:
            - subscription_key: The subscription_key given in the generate model step.
    
            Returns a list of status. The task is done if all status are "Done".
            If "Failed" showed up, the generating process failed.
            This is a polling API, so only proceed if the status are finally determined ("Done" or "Canceled").
    
        For Hyper3D Rodin mode FAL_AI:
            Parameters:
            - request_id: The request_id given in the generate model step.
    
            Returns the generation task status. The task is done if status is "COMPLETED".
            The task is in progress if status is "IN_PROGRESS".
            If status other than "COMPLETED", "IN_PROGRESS", "IN_QUEUE" showed up, the generating process might be failed.
            This is a polling API, so only proceed if the status are finally determined ("COMPLETED" or some failed state).
        """
        try:
            blender = get_blender_connection()
            kwargs = {}
            if subscription_key:
                kwargs = {
                    "subscription_key": subscription_key,
                }
            elif request_id:
                kwargs = {
                    "request_id": request_id,
                }
            result = blender.send_command("poll_rodin_job_status", kwargs)
            return result
        except Exception as e:
            logger.error(f"Error generating Hyper3D task: {str(e)}")
            return f"Error generating Hyper3D task: {str(e)}"
  • Documentation in the asset_creation_strategy prompt explaining usage of poll_rodin_job_status tool.
        - Use poll_rodin_job_status() to check if the generation task has completed or failed
    3. Import the asset
Behavior4/5

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

With no annotations provided, the description carries full burden and does well by disclosing key behavioral traits: it's a polling API that should only proceed when status is finally determined, it returns status lists or single status depending on mode, and it explains what different status values mean (Done, Failed, COMPLETED, IN_PROGRESS, etc.). It doesn't cover rate limits, authentication needs, or error handling details.

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

Conciseness3/5

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

The description is appropriately sized but could be more front-loaded. The first sentence states the purpose clearly, but the detailed mode-specific information follows in a somewhat repetitive structure. Some redundancy exists in explaining polling behavior twice for different modes. Every sentence adds value, but organization could be more efficient.

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?

Given the tool's complexity (two operational modes with different parameters and return formats), no annotations, and no output schema, the description does a good job covering essential information. It explains what the tool does, when to use it, parameter meanings, return value interpretation, and polling behavior. It doesn't specify exact return formats or error cases, but provides sufficient context for correct usage.

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

Parameters5/5

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

With 0% schema description coverage, the description fully compensates by explaining both parameters in detail: subscription_key is for MAIN_SITE mode and comes from the generate model step, request_id is for FAL_AI mode and also comes from the generate model step. It clarifies the exclusive relationship between these parameters based on the mode being used.

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 tool checks if a Hyper3D Rodin generation task is completed, specifying the verb 'check' and resource 'task status'. It distinguishes from siblings like 'get_hyper3d_status' by focusing on Rodin mode specifically, though it doesn't explicitly contrast with 'poll_hunyuan_job_status' which has a similar polling function for a different service.

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 for when to use this tool: after initiating a generation task in Hyper3D Rodin mode, using parameters from that step. It distinguishes between MAIN_SITE and FAL_AI modes with specific parameter requirements. However, it doesn't explicitly state when NOT to use it or mention alternatives like 'get_hyper3d_status' for non-Rodin tasks.

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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