poll_rodin_job_status

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

With no annotations provided, the description discloses key behavioral traits: it returns a list of statuses (MAIN_SITE) or a single status (FAL_AI), defines terminal states ('Done', 'Canceled', 'COMPLETED', or failed states), and warns about polling semantics. This goes beyond a simple 'check status' and effectively communicates the tool's behavior.

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

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

The description is organized into clear sections by mode, with every sentence providing useful information. It is appropriately detailed for the complexity of two modes and avoids redundant or filler content. The structure makes it easy to scan and parse.

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

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

The description fully covers the tool's purpose, parameter usage, status interpretation, and polling behavior for both modes. Given the lack of output schema, it also explains return values and success/failure criteria. This is complete for the tool's complexity and does not leave obvious gaps.

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

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

Schema description coverage is 0%, so the description must add meaning to the parameters. It does exactly that by explaining that 'subscription_key' comes from the generate model step for MAIN_SITE mode and 'request_id' for FAL_AI mode. This clarifies the purpose of each parameter beyond the bare schema definitions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

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) and specifies the resource and verb, differentiating it from sibling polling 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.

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

The description provides explicit guidance on how to interpret statuses and when to proceed, stating 'This is a polling API, so only proceed if the status are finally determined.' It explains the success/failure conditions for each mode, though it does not explicitly name alternative tools. The context is clear enough for an agent to know when to use this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.