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

Annotations already mark the tool as read-only, so no safety disclaimer is needed. The description adds substantive behavioral context by disclosing what the tool computes and returns: cohort median/range, price position, ML guide reference, seller risks with their exact phrase, and similar cars. It does not cover error handling, but the read-only annotation lowers that burden.

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 two sentences with no filler: the first front-loads the resource and lists specific data fields, the second clarifies the accepted input form. The enumeration is dense but each item adds concrete information about what the tool returns.

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 one required parameter, read-only and open-world annotations, and no output schema, the description covers the essentials: how to pass the input (key or URL) and exactly what the response will contain (listing facts, cohort comparison, ML reference, seller risks, similar cars). No critical calling information is missing.

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?

The schema provides only a string constraint for 'key' with 0% description coverage, so the description must compensate. It does so by stating that the parameter accepts either a bare key or the full URL, and it shows the URL pattern with the <key> placeholder. This meaningfully resolves the ambiguity, though it does not fully define the key's format on its own.

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 title 'Ver un auto en detalle' plus the description 'Ficha de un aviso de auto usado' clearly identifies a detail-view operation for a single used-car listing. The enumerated contents (version, engine, km, cohort stats, price position, ML guide reference, seller-declared risks, similar cars) make it easy to distinguish from siblings like search_used_cars or car_model_prices.

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?

Usage is implied rather than explicit: the tool is clearly meant for when you already have a specific listing key or URL and want its full detail sheet. However, it never explicitly says when to choose this over siblings like search_used_cars or car_declared_risks, nor does it state exclusions.

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