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get_mainline_route_per

Retrieve monthly passenger statistics for mainline train routes by specifying year-month and route name.

Instructions

간선열차 노선별 이용인원 통계 (갱신: 매월 1일, M-2). run_ym=운행연월(YYYYMM), rte_nm=노선명

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rte_nmNo
run_ymNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Install Server

TDQS

A3.5/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of disclosing behavior. It does mention the update frequency (monthly, M-2), which is useful for interpreting data freshness. However, it does not state read-only nature, permission requirements, return format, pagination, or any side effects. Given it's a data retrieval tool, the lack of behavioral clarity is a notable gap.

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?

The description is two short sentences, with the purpose stated first and parameter semantics following. It contains no redundant information or fluff. Every element earns its place, and the structure is front-loaded for quick comprehension.

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 simple two-parameter tool and the presence of an output schema (which handles return format), the description covers the essential context: purpose, parameter meanings, and update cadence. It doesn't explain potential constraints like required fields or typical values, but for a straightforward lookup tool this is adequate. Some details about expected response structure could be added, but the output schema mitigates that.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has zero description coverage, so the description must explain the parameters. It does so explicitly: 'run_ym=운행연월(YYYYMM)' provides both meaning and format, and 'rte_nm=노선명' explains the route name parameter. This fully compensates for the schema's lack of information and leaves no ambiguity.

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 provides passenger usage statistics by route for mainline trains ('간선열차 노선별 이용인원 통계'). It specifies the resource (mainline routes) and the metric (passenger counts), distinguishing it from sibling tools like get_mainline_station_per (by station) or get_wide_rail_route_per. It lacks an explicit verb like 'retrieve' but the intent is unmistakable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is given on when to use this tool versus the many sibling statistics tools. The description only states what it provides and the update schedule; it does not mention alternative tools or conditions under which this one should be preferred. An agent would have to infer usage from the name and context, which is error-prone given the large sibling set.

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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