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poll_rodin_job_status

Poll the Hyper3D Rodin generation task status to know when it completes or fails. Provide the subscription_key or request_id from the generate step.

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
Behavior4/5

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

With no annotations, the description fully discloses that it is a polling API, explains status meanings and final states, and indicates return formats. It could add info on rate limits or cancellation.

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 with clear sections for each mode, but some information is repeated (e.g., polling nature mentioned twice). It could be slightly more concise while remaining clear.

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 the complexity of two modes and two parameters, the description covers all necessary information: parameter usage, status meanings, polling stop conditions, and return values. No output schema exists, but the description compensates.

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?

Despite 0% schema coverage, the description thoroughly explains each parameter's purpose and which mode it applies to (subscription_key for MAIN_SITE, request_id for FAL_AI), adding significant value.

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 clearly states the tool checks if Hyper3D Rodin generation is completed, with distinct handling for two modes. The verb 'poll' and resource 'job status' are specific and distinguish it from sibling tools like poll_hunyuan_job_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 provides clear context on when to stop polling (status determined) and what constitutes success/failure for each mode. However, it does not explicitly mention when not to use this tool or 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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