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poll_rodin_job_status

Poll the status of a Hyper3D Rodin generation job until completed or 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
request_idNo
subscription_keyNo
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It describes polling nature, expected statuses, and final states, but omits details like rate limits, timeouts, or retry behavior. The behavior is adequately described for a basic polling tool.

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 per mode, but it is somewhat verbose. Each sentence adds value, but consolidating could improve readability. Front-loading the purpose is good.

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 no output schema, the description provides return value interpretation and final states. It covers the two modes adequately but could add guidance on error handling for non-standard statuses. Overall sufficient for the tool's complexity.

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 description coverage is 0%, so the description must compensate fully. It does so by explaining each parameter (subscription_key for MAIN_SITE, request_id for FAL_AI) and their source from the generate step, adding significant meaning 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 clearly states the tool checks if a Hyper3D Rodin generation task is completed. It distinguishes between two modes (MAIN_SITE and FAL_AI) with different parameters and statuses, specifying the verb 'poll' and resource '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 explains when to use the tool (after generation) and how to interpret statuses, with clear polling logic. However, it does not explicitly compare to sibling polling tools like poll_hunyuan_job_status or get_hyper3d_status, which could help an agent choose.

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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