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Rotate Pilot — FAA exam prep

Decode a METAR

decode_metar
Read-onlyIdempotent

Decodes a METAR aviation weather report into plain English: wind, visibility, weather, clouds, ceiling, temperature/dew point, altimeter and the VFR/MVFR/IFR/LIFR flight category. Pass either the raw METAR text or a 4-letter ICAO airport code to fetch the latest report from NOAA's Aviation Weather Center. For training, not for flight planning.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
icaoNoICAO airport code, e.g. KJFK. Used when metar is not given.
metarNoRaw METAR/SPECI text, e.g. 'KJFK 261751Z 18012KT 10SM FEW250 24/14 A3002'.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so safety is covered. The description adds meaningful behavioral context: fetching the latest report from NOAA's Aviation Weather Center and the disclaimer that it is training-only, not for flight planning. There is no contradiction with annotations.

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?

Two sentences, no filler, with the core purpose and output fields front-loaded. The invocation guidance and safety caveat follow naturally. Every sentence earns its place.

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?

For a simple decode tool with no required parameters, no output schema, and strong read-only/idempotent annotations, the description is complete. It specifies inputs, behavior, output contents, and the training-only constraint. Nothing necessary for correct invocation is missing.

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%, with both 'icao' and 'metar' already documented including an example. The description adds the either/or relationship and explains that an ICAO code fetches the latest report, but it largely reinforces what the schema already provides.

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 opens with a specific verb and resource: 'Decodes a METAR aviation weather report into plain English'. It enumerates the decoded fields (wind, visibility, weather, clouds, ceiling, temperature/dew point, altimeter, flight category), which clearly distinguishes it from siblings like decode_taf.

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 clearly states how to invoke the tool ('Pass either the raw METAR text or a 4-letter ICAO airport code') and provides an important operational caveat ('For training, not for flight planning'). It does not explicitly mention alternatives or when not to use it, but the context is clear enough for an agent to proceed.

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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