get_station_transfer_info

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does disclose the data snapshot date, the number of stations (93), the filtering behavior (partial match), and the default of returning all records. This is useful. However, it does not describe the output structure (though an output schema exists), nor any error behavior, permissions, or side effects. It also does not explicitly state that the operation is read-only. description adds context but leaves some behavioral aspects unaddressed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and well-structured: the first sentence states the core purpose and data source, followed by included data, then parameter explanations, then default behavior, and finally English/Japanese translations. The translations add length but are useful for international agents. The purpose is front-loaded, and the content is logically ordered with no fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (2 optional params, output schema present), the description covers purpose, parameters, defaults, and data scope. However, it omits details that could be important: how multiple filters combine (if both are given), whether results are paginated, and what happens if no matches are found. The output schema likely covers return structure, but the description does not address these edge behaviors. It is adequate but not fully complete.

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

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

The input schema provides no descriptions (coverage 0%), so the description must compensate. It does so by explaining each parameter: station_name and line_name both support partial match, with examples ('서울', '동대구' and '경부고속', '호남선'). It also states that omitting both returns all records, covering default behavior. This provides clear semantics beyond the bare parameter names and default empty strings.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the purpose: '역별 타 교통수단과 환현황 조회' (inquiry of transfer status to other transportation modes by station). It specifies the data source (odcloud), date (2024.12.31), and scope (93 stations), and mentions the included data elements (KTX, metropolitan railway, urban railway, transfer parking lots). This is a specific verbresource. However, it does not explicitly differentiate from the sibling tool 'get_urban_transfer_info', so the purpose is clear but sibling distinction is not fully articulated.

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

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

The description provides usage context for the parameters (partial match, examples) and the default behavior when no input is given ('미입력 시 전체 반환'). It tells the agent how to filter and what to expect., it does not mention when to choose this tool over alternatives like get_urban_transfer_info or search_station, nor does it state any exclusions. The guidance is partial but not absent.

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