get_price_distributionRetrieve the price distribution (min, quartiles, median, max) for similar active car listings to benchmark a vehicle's market price.
Faixa de preços (mínimo, p25, mediana, p75, máximo) de anúncios ativos semelhantes. Use para dar contexto de preço. (year_tolerance ±anos, padrão 1, máx 5.)
| Name | Required | Description | Default |
|---|---|---|---|
| car_id | Yes | ||
| year_tolerance | No |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds the exact output structure (min, p25, median, p75, max) and the year tolerance bounds, which goes beyond what annotations provide. There is no contradiction between description and annotations.
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 concise and front-loaded: it states the output, the intended use, and the key parameter constraint in two short sentences. Every element adds value without redundancy.
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?
The description includes the return values and the parameter bounds, which is sufficient for a tool with no output schema. It does not elaborate on what 'similar' means or any additional constraints, but for a price-context tool this is likely adequate. Minor gap: it does not clarify whether the results are based on the car_id alone or other criteria, but the annotation openWorldHint=false suggests closed-world behavior.
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 description coverage is 0%, so the description must compensate. It explains year_tolerance with default and max values, and it implies car_id is used to identify the vehicle for finding similar listings. While car_id is not explicitly described, its role is clear from the context of 'similar active listings.' This is adequate compensation given the tool's simplicity.
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 the tool provides a price range (min, p25, median, p75, max) for similar active listings. It also gives the intended use ('dar contexto de preço'). It does not explicitly differentiate from sibling tools like get_market_stats or get_fipe_valuation, but the focus on 'similar active listings' and the specific output quantiles makes its purpose distinctive.
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 an explicit usage context ('Use para dar contexto de preço') and provides parameter guidance for year_tolerance (default 1, max 5). It does not state when not to use this tool or name alternatives, but the provided context is sufficient for an agent to decide when this is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.