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

Annotations already cover readOnlyHint and openWorldHint, and the description builds on that by disclosing the internal data-quality pass (each opportunity checked for active card, same price, and absence of crash/recovery/debt/foreign plate), the output contents (gap %, conservative gap, sample stats, comparables with links) and the tier distinction. None of these behaviors are visible from annotations alone.

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 yet efficient, front-loading the core premise (below-cohort price), then the verification pass, then the output payload and tier semantics. Every sentence carries distinct information with no filler, though the density of technical jargon (cohort, brecha conservadora, p25/mediana/p75) may slow comprehension 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?

Given high complexity (14 optional filters, no required params, no output schema), the description does a good job of explaining the returned data and the strict/exploratory dichotomy. However, it omits practical aspects such as pagination behavior (page/limit interplay), how filters interact with the fixed-cohort matching, and the scale/ordering implied by 'sort', leaving gaps for a multi-parameter open-world query tool.

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 only 29% across 14 parameters, so the description bears the burden of explaining filters, but it only clarifies the 'tier' parameter and the 'brecha' concept. The other 13 parameters (body, fuel, sort, seller, kmMax, yearMin, department, etc.) go unexplained, leaving a large gap where the description should compensate for the sparse 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 states a precise verb+resource: finding cars priced below their fixed cohort (same model, year, version, engine, transmission within a km band). This clearly differentiates it from siblings like car_market_report, car_model_prices, search_used_cars and get_car by describing its specific matching logic rather than generic search or reporting.

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 explains the tier semantics (strict = solid evidence, exploratory = to explore) and the qualifying criteria, giving clear context for when the tool applies. However, it does not explicitly name sibling alternatives (e.g., search_used_cars for general browsing) or state when NOT to use this tool, leaving routing to inference.

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