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

Annotations already declare readOnly, idempotent, non-destructive, open-world, so the safety profile is covered. The description does add value by disclosing the response shape — textual seller phrase, severity, and the discount measured against the clean cohort — which is behavioral context the annotations can't carry. It says nothing about pagination, volume of results, or what happens when no clean cohort exists for a listing.

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?

Two sentences: a dense but front-loaded statement of what is returned, followed by a short purpose clause. Every element (risk types, severity, discount baseline, category summary, use cases) earns its place. The first sentence is long and comma-heavy, which slightly hurts scannability.

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 14 optional parameters, no output schema, and read-only annotations, the description compensates well by explaining what the results contain and how the discount is computed (against cars declaring nothing). The main residual gap is the optional `onlyMeasured` flag and how cohort-matching affects results, which is only implied by the 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?

Schema coverage is 100% with 6 enums already fully documented, so the schema carries parameter meaning. The description only hints at filtering indirectly by listing risk categories that match the `category` enum, adding no format or syntax detail beyond the schema. Baseline 3 applies when the schema does the heavy lifting.

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 gives a specific verb+resource: it surfaces listings whose seller DECLARES a risk, enumerating the seven risk categories (deuda, papeles, siniestro, recupero, mecánica, chapa extranjera, uso intensivo) and the return payload (textual phrase, severity, discount vs. clean cars, per-category summary). This clearly separates it from generic siblings like search_used_cars or get_car. It stops short of naming a sibling directly, so it is clear but not sibling-differentiating in explicit terms.

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 closing sentence gives concrete use cases: to understand the discount on a car with debt, or to rule out risks. That is clear context for when to reach for this tool. It does not state when NOT to use it or point to an alternative such as search_used_cars for clean results, which keeps it below a 5.

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