create_analysis_batch

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

The description discloses important behavioral details beyond annotations: the first prompt is full price and each additional is 50% off, the result includes a pricing summary, and each analysis id must be polled individually. Since annotations only provide generic flags (readOnlyHint=false, destructiveHint=false), the description carries the transparency burden well. A slight gap is that it doesn't explicitly mention a credit deduction or that this creates persistent resources, but the pricing information strongly implies it.

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 sentences, each earning its place: main action, pricing incentive, and follow-up/alternative guidance. The most important info is front-loaded, and no filler words exist.

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 covers the creation call, pricing, return structure, how to retrieve results, and when to use an alternative. With an output schema present, the tool is fully specified for an agent to invoke correctly without guesswork.

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?

Input schema covers 100% of parameter descriptions, so the baseline is 3. The description reinforces the prompts parameter with the pricing tier (first full, additional 50%) which is already stated in the schema. It does not add new meaning for video_id, model, or metadata beyond what the schema provides.

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: "Run 2–10 prompts against the SAME video in one call" and explicitly names the endpoint POST /v1/analyses/batch. It clearly differentiates from siblings by emphasizing batch execution on the same video, which is the unique capability versus create_analysis or validate_analysis.

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 explicitly states when to use this tool: "always cheaper than separate create_analysis calls for multi-question workloads," and tells the user to use validate_analysis for pre-checking assessability, and to poll with get_analysis or wait_for_analysis for individual results. It clearly contrasts with alternatives and gives direct guidance.

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