check_video

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 does convey the essential behavior — this is a status probe whose useful output only materializes when generation completes — but it says nothing about possible status values, whether repeated polling is safe/rate-limited, or behavior on an invalid or expired ID.

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 plus a one-line Args note; the purpose and the outcome are front-loaded and nothing is redundant.

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, read-style polling tool with an output schema covering return values, the description is nearly sufficient: purpose, parameter origin, and result are all covered. Only polling/status semantics are 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 0%, so the single parameter is undocumented in the schema, but the description compensates by explaining the parameter's origin and meaning: it is the prediction identifier returned by generate_video. That is exactly the semantics an agent needs to pass the right value.

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?

States a specific verb and resource — check the status of a video generation job by ID — and adds the outcome (a link once it is ready). It hints at ordering by saying the ID comes from generate_video, but never distinguishes itself from download_video, which is the natural next step.

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 Args note 'ID, который вернул generate_video' establishes the precondition and workflow position: call this after generate_video using the returned prediction_id. It gives no exclusions, no polling cadence, and no pointer to download_video for retrieving the finished file.

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