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by com.gaduin
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Airline on-time record

get_airline_stats
Read-onlyIdempotent

An airline's last 30 days of the flights it operates itself: arrivals, on-time and late counts with the on-time share, cancellations, diversions, median and 90th-percentile arrival delay, routes flown, its most and least delayed flights, the late rule, and a link to its airline page on gaduin.com.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "code": "<code>"
    },
    "name": "get_airline_stats"
  }
}

Input Schema

NameRequiredDescriptionDefault
codeYesAirline IATA code (e.g. BA) or ICAO code (e.g. BAW).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, and open-world, so the safety profile is covered. The description adds genuinely new behavioral context: the fixed 30-day window, the metric set including the 'late rule,' and an outbound link to gaduin.com. It does not state behavior for an unknown or invalid airline code.

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?

One dense sentence that front-loads the scope (airline, 30 days, own-operated flights) before listing metrics. Every clause carries information, though the long comma-separated list of metrics is harder to scan than a short structured enumeration.

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 usefully serves as the return-value specification by listing the fields an agent will get back. For a single-parameter read tool with full annotation coverage, little is missing; only error behavior and the precise meaning of 'late rule' are unspecified.

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% and the single parameter's IATA/ICAO format is fully documented in the schema, so the description adds nothing about inputs. Baseline 3 applies when the schema carries the whole parameter burden.

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 names a specific resource (an airline's 30-day on-time record) and enumerates its contents, which distinguishes it from flight-level tools like get_flight_status and airport-level tools like get_airport_status. The phrasing is a noun phrase rather than a verb+resource statement, so the action must be inferred from the name.

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 the scope phrase 'flights it operates itself' and 'last 30 days,' which tells an agent this is an airline-level rollup excluding codeshare. There is no explicit when-to-use guidance or named alternative to choose instead.

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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