get_request_status

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

With no annotations provided, the description carries the transparency burden. It communicates that this is a read/status retrieval operation rather than a mutation, and that it relates to async requests. It does not disclose polling behavior, possible statuses, or whether the request must be complete, but it provides a reasonable baseline.

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?

Two short sentences, no filler, and the key purpose is front-loaded. Every word earns its place.

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?

For a single-parameter tool, the description covers the essential use case but lacks detail on what the status response looks like, especially since there is no output schema. It is adequate but not fully complete for an agent that may need to interpret the result.

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?

The schema already documents request_id fully, including its source ('returned from infer tool'). The description adds no parameter-specific meaning, but since schema coverage is 100%, the baseline of 3 applies.

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 action ('Check the status') and the resource ('an inference request'), and adds that it retrieves results of async requests. It does not explicitly name sibling tools, but the async framing distinguishes it enough from infer.

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 gives clear usage context: use this after an async inference request to get its results. It does not explicitly state when not to use it or name alternatives, but the intended scenario is clear.

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