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

Even with readOnlyHint=true and destructiveHint=false already present, the description adds substantial behavioral detail: de-identification guarantees, explicit PII exclusions, a 402 behavior when unpaid, pricing by record, and the existence of a sample/schema endpoint. This gives the agent a realistic model of what will happen before calling the tool.

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 long but information-dense, covering dataset contents, PII exclusions, filtering, payment, failure behavior, and a sample endpoint in a logical order. Every sentence contributes useful guidance, though some phrasing such as 'people and their AI assistants made here' could be trimmed without losing meaning.

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 tool with no output schema, the description covers what an agent needs: data contents, privacy safeguards, filtering, payment methods, and the no-payment response. It does not spell out the exact response shape or date formats, but it points to /data.json for the schema and sample, which fills the remaining 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 only 36%, so the description must compensate. It does so by enumerating the filter parameters (state, since, until, door, vendor) and pagination parameters (limit, offset), and by mapping payment methods to the relevant parameters (buyer_key, x402, MPP, AP2). It does not specify date formats or door/vendor value constraints, but it adds meaning well beyond the bare schema names.

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 it exposes the de-identified demand dataset of auto insurance requests, with a specific list of fields and outcomes. It is distinct from siblings like pull_requests or get_quotes because it positions this as the purchasable market dataset. The title and verb 'Buy' plus 'the demand dataset' make the resource unmistakable.

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 gives clear operational context: filter by state/since/until/door/vendor, paginate with limit/offset, and pay via buyer key, x402, MPP, or AP2. It also explains that without payment the tool returns a 402 with price and preview count, so an agent knows how to handle the no-payment case. It does not explicitly name alternative sibling tools or say when not to use them, 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.