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BlenderMCP

by kjanat

poll_rodin_job_status

Check if a Hyper3D Rodin generation task is completed by submitting the subscription key or request ID, and retrieve the final status.

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
request_idNo
subscription_keyNo
Behavior5/5

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

With no annotations, the description carries the full burden and does an excellent job. It lists all possible statuses ('Done', 'Failed', 'Canceled' for MAIN_SITE; 'COMPLETED', 'IN_PROGRESS', 'IN_QUEUE', and failure states for FAL_AI) and how to interpret them, making behavior fully transparent.

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

Conciseness5/5

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

The description is well-structured by mode, using clear bullet points for parameters and statuses. Every sentence adds value, and the length is appropriate for the complexity of covering two modes.

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

Completeness5/5

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

Given no output schema, the description explains return values and status interpretation for both modes, including final-state conditions. It is complete for a polling tool, covering success, failure, and in-progress scenarios.

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?

Schema coverage is 0%, so the description must explain parameters—and it does. It specifies that subscription_key is for MAIN_SITE and request_id for FAL_AI, both 'given in the generate model step,' adding critical usage context beyond the schema.

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 'Check if the Hyper3D Rodin generation task is completed,' clearly stating the tool's function. It distinguishes between MAIN_SITE and FAL_AI modes, setting it apart from sibling tools like poll_hunyuan_job_status or get_hyper3d_status.

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 explicitly says 'This is a polling API' and instructs to proceed only when statuses are final, giving clear context on usage. It details which parameter to use for each mode, though it doesn't explicitly reference alternative 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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