get_captions

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

Annotations already cover readOnly and idempotent behavior, so the description adds value by disclosing the segment-and-timestamp output model and the prerequisite captions feature. It does not contradict annotations and provides behavior beyond the structured fields.

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?

Three short paragraphs each carry distinct information: what the tool returns, how to scope it, and what feature it requires. There is no filler or repetition.

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 read-only tool with an output schema and annotations, the description covers the core selection and invocation context: purpose, scoping parameters, and feature prerequisite. It omits explanation of rationale and max_results, but those gaps are minor given the schema defaults and output schema.

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?

With 0% schema description coverage, the description should compensate for undocumented parameters. It adds meaning for start/end ('narrow results'), but it does not explain video_id, rationale, or max_results, leaving several parameters dependent on schema names/defaults.

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 opens with a specific verb and resource ('Get AI-generated visual descriptions of what happens on screen') and clarifies the use case ('understand the visual content without watching'), which distinguishes it from transcript-based or scene-based siblings. Even without naming a sibling, the visual-caption framing removes ambiguity.

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 says to use this tool when you need to understand visual content without watching, and it notes that start/end narrow results and that captions require the qa_only or full pipeline feature. It does not explicitly name alternatives or exclusions, so it stops short of a 5.

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