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NewKwLab Tools

lookup_airport

Look up an airport by IATA, ICAO or local code in the OurAirports public-domain database (86k+ airports): name, coordinates, elevation, country, municipality and runway summary.

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": "lookup_airport"
  }
}

Input Schema

NameRequiredDescriptionDefault
codeYesAirport code, e.g. JFK, KJFK, LHR

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the full burden; it does disclose that the data comes from the public-domain OurAirports database with 86k+ airports and that the result is descriptive metadata, implying a safe read-only call. It does not state behavior for ambiguous codes (e.g. a string matching both an IATA and a local code) or for codes not found, which are the main behavioral risks here.

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?

One front-loaded sentence that states the action, the accepted identifiers, the data source and the return payload with no filler. The enumeration of returned fields earns its place because no output schema exists.

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?

Because there is no output schema, the description appropriately enumerates the returned fields and names the underlying dataset, which is enough to call the tool correctly for a one-parameter lookup. The remaining gap is edge-case behavior (not-found, ambiguous or multi-type matches) that an agent calling with a plain code string would want to know.

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?

With a single parameter at 100% schema coverage the schema already documents `code`, and the description adds meaningful information beyond it by naming 'local code' as an accepted identifier type, which the schema's examples (JFK, KJFK, LHR) do not mention. It stops short of saying how precedence is resolved when a string could match more than one code system.

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 gives a specific verb and resource ('Look up an airport') and enumerates exactly which identifiers are accepted (IATA, ICAO, local code) plus the returned fields. It does not name the sibling search_airports, so the distinction between exact-code lookup and a search tool must be inferred from the wording 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 rather than stated: 'by IATA, ICAO or local code' signals a single-exact-code lookup, which indirectly separates it from search_airports, but there is no explicit when-to-use, when-not-to-use, or fallback guidance if the code is unknown.

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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