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Fair Fare: Was I overcharged? Check a fare that was paid

fairfare_check_fare
Read-onlyIdempotent

Fair Fare. Was I overcharged? Check a fare that was paid. Compares what was paid with the official meter tariff, the airport flat fare or New York's typical Uber and Lyft prices for the same trip and hour, gives a verdict (fair, high or overcharged), the next steps for that company or city regulator, and a short message to send asking for a refund.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoWhere it ended.
cityNoTariff city id, when giving miles instead of from and to.
fromNoWhere the trip started.
kindNoKind: taxi, uber, lyft, bolt or minicab. Defaults to taxi.
paidYesWhat was paid, without the tip, for example 48.50.
whenNoWhen the trip starts, in local time: now (the default), a time like 18:30 or 6pm, or a date and time like 2026-10-09T18:30.
milesNoTrip length in miles, instead of from and to.
minutesNoTrip time in minutes, if known.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint, so safety is covered. The description adds genuinely useful behavioral context by disclosing the output contents (verdict, next steps, and a refund message). It says nothing about prerequisites such as needing either from/to or miles plus a city, which matters for an 8-param tool.

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 purpose is front-loaded in the first two sentences and the return contents follow efficiently. The opening 'Fair Fare. Was I overcharged?' partially duplicates the title, which is the only minor waste.

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

Completeness4/5

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

With no output schema, the description correctly compensates by describing what comes back: a verdict, next steps for the regulator, and a refund message. Combined with 100% schema coverage this is close to complete, missing only an explicit note on required input combinations.

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 description coverage is 100%, so every parameter is already documented in the input schema. The description mentions the tariff/airport/Uber comparison but adds no syntax, defaults, or format details beyond what the schema provides, so baseline 3 applies.

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

Purpose4/5

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

The description states a specific verb and resource ('check a fare that was paid') and spells out the comparison basis (official meter tariff, airport flat fare, or typical Uber/Lyft prices). It is clear the agent is analyzing a past trip, not estimating a future one. It does not, however, name or rule out the sibling fairfare_estimate_fare, so differentiation is inferred from the name rather than stated.

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

Usage Guidelines3/5

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

Usage is implied by 'Was I overcharged?' and 'Check a fare that was paid', which signals the retrospective-dispute scenario. There is no explicit when-not guidance and no reference to alternatives such as estimate_fare for prospective trips, leaving the agent to infer the boundary.

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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