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

Beyond the readOnlyHint annotation, the description discloses the maximum 240-second wait, the no-reprocessing behavior, and that the tool does not resubmit tasks. This adds meaningful behavioral context not present in annotations, though it does not describe edge-case failure 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 a single compact sentence that front-loads the core purpose and immediately includes the most important constraints: job_id source, 240-second wait, and no resubmission. Every clause 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?

Given this is a simple one-parameter status query with an output schema already present, the description covers all necessary operational details: valid job_id sources, wait behavior, and idempotency expectations. Nothing critical is missing.

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 100%, and the input schema already fully explains that job_id is the speech-to-text task ID, where to obtain it, and not to pass video_id or links. The description does not add meaning beyond the schema, so baseline 3 is appropriate.

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 queries the status of a YouTube speech-to-text job by job_id, using a specific verb ('查询') and resource ('任务状态'). It is easily distinguishable from the sibling submit tools, which create jobs rather than poll 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?

It explicitly says to use a user-provided job_id or one returned by the submit tool, and tells the agent not to resubmit or trigger reprocessing. This provides clear conditions for use and explicitly warns against the main misuse.

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