Mileage context
get_mileage_contextAvalia se a quilometragem deste carro é alta ou baixa para o modelo/ano (mediana do mercado + km/ano).
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| car_id | Yes |
get_mileage_contextAvalia se a quilometragem deste carro é alta ou baixa para o modelo/ano (mediana do mercado + km/ano).
| Name | Required | Description | Default |
|---|---|---|---|
| car_id | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the tool as read-only, idempotent, and non-destructive. The description adds the methodology (market median + km/year) but does not describe the output format (e.g., returns 'high'/'low' or a numeric score). It provides some extra context beyond annotations but not full behavioral detail.
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 a single, efficient sentence that front-loads the core purpose and adds the methodology in parentheses. No wasted words or redundant information.
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 simple read-only tool with one parameter and no output schema, the description conveys the essential purpose and method. It lacks explicit return-value details and error conditions, but given the tool's simplicity and annotations, it is largely adequate. Slightly more detail on the output would make it fully 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?
Schema description coverage is 0%, so the description must compensate for parameter meaning. However, it does not explicitly mention car_id or explain its role beyond the tool name. The agent must infer that car_id identifies the car being evaluated, which is a gap for a single-parameter tool with no schema descriptions.
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's purpose: to assess whether a car's mileage is high or low for its model/year, using market median and km/year. It is specific and distinguishes from siblings by focusing solely on mileage context.
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 implies usage for mileage evaluation but does not explicitly state when to prefer this over alternatives like get_market_position or get_market_stats. No exclusions or alternative routing are provided, leaving some ambiguity among the many sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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