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

Beyond the annotations (readOnly=false, destructive=false, openWorld), the description discloses key behavioral traits: no charge is made, the clip list is frozen, and a private order_token is returned. It doesn't cover quote expiry or repeated-call/idempotency behavior, which would matter given idempotentHint=false.

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 core purpose and the returned token are front-loaded, and each sentence carries actionable instruction. The final sentence is a dense display checklist but still earns its place as buyer-facing guidance; it could be trimmed slightly.

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?

With no output schema, the description supplies the crucial return detail (private order_token) and the freeze/no-charge semantics, which is enough to call the tool correctly. Missing quote validity/expiry and how the token is subsequently redeemed leaves a small gap.

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 83%, so the schema already documents most parameters well, including the work-email rule and intended_use range. The description adds only the buyer-interaction workflow rather than new semantics for tier, media_resolution, or filters, so 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 states a specific verb and resource ("Create a fixed-price dataset quote for a filtered subset") and explicitly names the return artifact ("private order_token"), plus a scoping behavior ("Freezes the exact clip list"). This distinguishes it from siblings like scope_training_dataset and create_dataset_checkout without needing to open their schemas.

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 gives a clear workflow: ask the buyer for email/org/intended use first, then show tier, clip count, hours, price, payment method and agreement before asking acceptance. It doesn't explicitly contrast with alternatives like scope_training_dataset or describe_training_dataset, so the 'when not to use' dimension is left implicit.

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