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CarGene

Get sales figures

get_sales_figures
Read-onlyIdempotent

Get the sales figures of a series. Returns {series_id, url, figures, cells, region_totals, coverage, lifetime}. figures are the rows as published, each with units, the source's own wording, the period, source_url and a verbatim source_excerpt. cells are the grid a figure may be summed into, one per series, country and calendar year; a null units on a cell means the sources disagree, never zero sold. region_totals sum years within one country only, so never add across countries or add a parent region to its children. coverage rows are the blanks that were checked and found empty, with the reason. lifetime rows are cumulative or per-generation totals that must not be added to the grid. A model_id narrows figures only, since allocating a year to a generation needs the whole series. An empty list means not researched yet, never zero.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
model_idNoGeneration (model) id (a UUID from search_vehicles). Takes precedence over series_id when both are given.
series_idNoSeries id (a UUID from search_vehicles).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the annotations (readOnlyHint, idempotentHint), the description discloses crucial data behaviors: null units mean disagreement, never zero; empty lists mean not researched, never zero; region_totals must not be summed across countries; lifetime rows must not be added to the grid. This prevents serious analytical errors.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long but tightly packed with essential semantics; the first sentence front-loads the purpose, and each subsequent clause explains a return field or a caveat. A few clarifications could be tightened, but no sentence is wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema present, the description carries the full burden of explaining return values, and it does so thoroughly: every returned field is defined, edge cases are handled, and parameter behavior is clarified. Nothing critical is missing for correct invocation and interpretation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already covers both parameters at 100%, so the baseline is 3. The description adds value by explaining why model_id narrows figures only and why the whole series is needed for year-to-generation allocation, which is not fully inferable from the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: 'Get the sales figures of a series.' It goes beyond a simple label by enumerating the exact returned fields and their meanings, making the tool distinctly recognizable from the sibling vehicle-focused tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives concrete usage context: exactly one of series_id or model_id should be passed, and model_id only narrows figures, not the series-wide allocation. It does not explicitly name alternative siblings, but the context makes the tool's role clear enough.

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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