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Glama

Find subway station

subway_station

Translate Seoul subway station names between English, Korean, Japanese, and Chinese with typo tolerance. Returns official names, lines, and coordinates.

Instructions

Look up a Seoul-area subway station by name in English, Korean, Japanese or Chinese (typos tolerated). Returns official names in each language, the lines serving it and coordinates. Use this to translate station names.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesStation name or landmark, e.g. 'gangnam', '강남', 'Hongdae'

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does reasonably well: it discloses accepted input languages, that typos are tolerated, and what the response contains (names per language, lines, coordinates). It says nothing about error behavior for unknown stations or any rate/scope limits, so it stops short of fully covering the behavioral profile.

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?

Three short sentences, front-loaded with the lookup action and immediately followed by input tolerance, return contents, and the primary use case. No filler or repetition.

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?

There is no output schema, so the description supplies the return shape itself (per-language official names, serving lines, coordinates), and the single input parameter is fully covered by the schema. Nothing needed to invoke it correctly is missing.

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?

Schema coverage is 100% for the single required query parameter, so the baseline is 3. The description adds value beyond the schema by stating that all four scripts are accepted and that typos are tolerated, which the schema description (examples only) does not convey.

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?

States a specific verb and resource ('look up a Seoul-area subway station by name') with a clear geographic scope. It implicitly separates itself from subway_route by focusing on name lookup rather than trip planning, but it never names or contrasts a sibling explicitly.

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?

One usage cue is given: 'Use this to translate station names.' That implies the intended scenario but offers no when-not guidance and does not mention how it relates to subway_route or korea_guide when an agent is choosing between them.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.