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

The description goes far beyond the annotations by disclosing de-identification protections, the exact fields included and excluded, payment methods, the 402-with-preview behavior without payment, and the availability of a sample schema. This is rich behavioral context that complements the readOnly/non-destructive hints.

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 dense but not bloated: each sentence contributes dataset scope, filters, pricing/payment, error behavior, or schema access. It could be easier to scan as structured bullets, but it is appropriately sized for the tool's complexity.

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 an 11-parameter, payment-gated tool with no output schema, the description covers the data content, de-identification guarantees, filters, pricing, payment modes, the no-payment 402 case, and a link to the full schema. It does not spell out exact output formatting or every parameter constraint, but the /data.json pointer and the level of detail make it sufficiently complete.

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 only 36% schema description coverage, the description carries most of the parameter meaning. It explains filter dimensions (state, since, until, door, vendor), pagination (limit, offset), and maps payment concepts to the relevant params (x402, MPP, AP2, buyer key). It does not fully specify value formats or how payment params are transported, but it adds substantial meaning beyond the bare schema.

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 identifies a specific resource—the de-identified demand dataset—and a concrete operation: retrieve/buy records with filtering and pagination. It enumerates the record fields and explicitly distinguishes this dataset from other possible tools by saying it covers every auto insurance request made here.

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 context for when to use the tool: to obtain demand records, with state/date/door/vendor filters, pagination, and payment requirements. It does not explicitly name sibling alternatives or say when not to use it, but the context is unambiguous enough for an agent to route to this tool for dataset access.

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