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get_rolling_stock_by_year

Retrieve KORAIL's annual rolling stock fleet counts from 2016 to 2024. Specify a year or leave blank to view all nine years, covering KTX, SRT, locomotives, passenger cars, and freight cars.

Instructions

연도별 차량보유현황 조회 (2024.12.31 기준, 2016~2024년 9개 연도). KTX·SRT·KTX-이음·디젤기관차·전기기관차·디젤동차·전기동차·간선형전기동차· ITX-청춘·객차·발전차·화차·기중기 차종별 연도별 보유 대수 포함. year: 조회 연도 (예: '2024', '2020'). 미입력 시 전체 9개 연도 반환. ※ SRT는 SR(수서고속철도) 소속으로 KORAIL 보유 수치에 포함된 것으로 표기됨.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Install Server

TDQS

A3.8/5.0
Behavior3/5

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

Annotations are absent, so the description carries the burden. It discloses the data scope and the SRT ownership caveat, which is useful. However, it does not state whether the operation is read-only, how invalid year values are handled, or any other behavioral traits. It is not contradictory, but leaves room for more detail.

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?

The description is concise and front-loaded with the main purpose, followed by the vehicle types and parameter guidance. The list of vehicle types is a bit long but necessary for completeness. No wasted words; slightly verbose but acceptable.

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?

Given the output schema exists, the description does not need to explain return format. It covers the tool's purpose, data coverage, parameter behavior, and the SRT nuance. Nothing critical is missing for an agent to call it correctly.

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 description coverage is 0%, so the description fully compensates for the year parameter. It explains the expected format, gives examples ('2024', '2020'), and specifies the default when omitted. This adds meaningful guidance beyond the bare schema.

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 clearly states the tool queries annual rolling stock holdings (연도별 차량보유현황 조회) and lists the specific vehicle types included. It conveys the resource and scope, but does not explicitly contrast it with any sibling tools, so it earns a 4 rather than a 5.

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 provides clear context: the available years (2016-2024), the year parameter with examples, and the default behavior when year is omitted (returns all 9 years). It does not mention when not to use this tool or suggest alternatives, so the lack of exclusions keeps it at a 4.

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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