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poll_rodin_job_status

Check completion status of Hyper3D Rodin AI model generation tasks in Blender. Monitor progress and determine when 3D models are ready for use or if generation failed.

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 decorated with @mcp.tool() that implements the poll_rodin_job_status tool. It forwards the request to the Blender addon by calling send_command with the appropriate parameters (subscription_key or request_id).
    @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)}"
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: it discloses this is a polling API (important behavioral trait), explains completion criteria for both modes, describes failure states, and provides specific status interpretation rules. It doesn't mention rate limits, authentication needs, or error handling details, but covers the essential polling behavior thoroughly.

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 not optimally structured. It front-loads the core purpose, but the mode-specific sections create some redundancy. Every sentence earns its place by providing essential information, but the formatting with bullet-like lists could be more streamlined for an AI agent.

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 complexity (two operational modes with different parameters and status interpretations), no annotations, and no output schema, the description provides substantial context. It explains what constitutes completion/failure for both modes, the polling nature, and parameter usage. It doesn't describe the exact return format or error responses, but covers the essential operational logic comprehensively.

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 context: 'subscription_key' for MAIN_SITE mode and 'request_id' for FAL_AI mode. It clarifies which parameter to use for which operational mode and ties them back to previous generation steps, adding significant semantic 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 tool's purpose: checking completion status of Hyper3D Rodin generation tasks. It specifies the exact resource (Rodin generation task) and verb (check/status). However, it doesn't explicitly differentiate from sibling 'get_hyper3d_status', which appears to serve a similar status-checking function.

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

Usage Guidelines5/5

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

The description provides explicit usage guidance: 'This is a polling API, so only proceed if the status are finally determined.' It distinguishes between two modes (MAIN_SITE and FAL_AI) with different parameters and status interpretations, effectively telling the agent when to use which parameter set and how to interpret results for each mode.

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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