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yevhen-kalyna

autoria-mcp

get_average_price_over_periods

Track monthly average car prices over customizable periods (30, 90, 180, 365 days). Filter by brand, model, year, mileage, and more to analyze Ukrainian market trends.

Instructions

Paid. Average-price time series (monthly) for a car or omni_id.

Same inputs and modes as get_average_price; returns graph_data (monthly average price, date as "MM.YY") plus the available period presets. Requires AUTORIA_USER_ID. period ∈ {30, 90, 180, 365}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyNoBody style name.
fuelNoFuel type name.
brandNoBrand name.
colorNoColour name.
driveNoDrive type name.
modelNoModel name.
periodNoPeriod in days; one of 30, 90, 180, 365.
regionNoRegion name.
gearboxNoGearbox name.
omni_idNoVIN, plate number, or advert id. Skips by-params mode.
year_toNoLatest year.
year_fromNoEarliest year.
mileage_toNoMax mileage in km.
mileage_fromNoMin mileage in km.
generation_idNoRaw generation id (improves accuracy). One only — facelifts are separate ids, so call once per generation to span them.
modification_idNoRaw modification id (improves accuracy).
engine_volume_toNoMax engine volume in litres, e.g. 2.1. Narrows the comparable sample, NOT the model-level headline estimate.
engine_volume_fromNoMin engine volume in litres, e.g. 1.9. Narrows the comparable sample, NOT the model-level headline estimate.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
quotaNo
cohortNo
noticeNo
periodNo
statusNook
graph_dataNo
period_selectorNo
Behavior4/5

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

No annotations exist, so the description carries full burden. It discloses the tool is paid, requires user ID, returns graph_data with monthly dates, and period options. No behavioral contradictions.

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

Conciseness5/5

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

The description is very concise: one short paragraph plus a list. Every sentence adds value, and key points are front-loaded. No wasted words.

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

Completeness3/5

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

Given 18 optional parameters, full schema coverage, and an output schema (not shown), the description links to get_average_price for input details, reducing burden. However, it does not fully explain all parameters or edge cases.

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

Parameters3/5

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

Schema coverage is 100%, so baseline is 3. The description adds minimal parameter context beyond the schema (e.g., period values, omni_id usage). Does not significantly extend meaning.

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 clearly states it returns a monthly average-price time series for a car or omni_id, and distinguishes itself from get_average_price by noting it returns graph_data. The verb+resource+scope are specific.

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 references get_average_price for input modes, implicitly guiding usage. It specifies the required AUTORIA_USER_ID and available period presets. However, it does not explicitly state when to choose this over other 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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