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Subway route

subway_route

Plan a Seoul subway trip between two stations, showing lines, transfers, boarding direction, time and fare. Accepts station names in English, Korean, Japanese, Chinese and landmarks; works offline.

Instructions

Plan a subway/metro trip in the Seoul Metropolitan Area (Seoul, Incheon, Gyeonggi) between two stations. Accepts station names in English, Korean, Japanese or Chinese, plus common landmarks (Hongdae, COEX, Incheon Airport). Returns lines to take, where to transfer, which direction to board, estimated minutes and fare. Works offline, no API key.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toYesArrival station, e.g. 'Seongsu', '성수'
fromYesDeparture station, e.g. 'Myeongdong', '명동', 'Incheon Airport T1'
allow_expressNoAlso consider express trains (Line 9, Line 1, Suin–Bundang…). Default false; express data is less complete.
airport_expressNoAllow the AREX direct train (Seoul Station ↔ Incheon Airport), which needs a separate ticket. Default false.
fewer_transfersNoPrefer fewer transfers even if slightly slower.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

No annotations are provided, so the description carries the burden, and it does disclose the return contents (lines, transfer points, boarding direction, minutes, fare) and an operational trait (works offline, no API key). It omits error behavior for unrecognized or ambiguous station names and says nothing about data freshness for fares/times.

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 sentences, zero waste: purpose and scope first, accepted inputs second, outputs and the offline capability third. Every sentence earns its place and the most important information is front-loaded.

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?

With no annotations and no output schema, the description compensates by describing both the operational model (offline, no key) and the return payload. For a read-only planning tool this covers everything an agent needs before calling it.

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%, so the schema already documents all five parameters and their defaults, putting the baseline at 3. The description adds genuine meaning by stating that station names are accepted in English, Korean, Japanese and Chinese and that landmarks like Hongdae, COEX and Incheon Airport are valid inputs — helpful beyond the schema's example strings.

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 — 'Plan a subway/metro trip ... between two stations' — plus a precise geographic scope (Seoul, Incheon, Gyeonggi). It is functionally distinguishable from subway_station, but it never names or contrasts with any sibling tool, so it falls short of the top tier.

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?

Usage context is clear: this is the tool for trip planning within the Seoul Metropolitan Area, accepting multi-language station names and landmarks. However, there are no explicit exclusions (e.g., 'not for other cities') and no routing to alternatives such as subway_station.

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