get_station_facilities

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. It does add a valuable caveat: '데이터기준일: 실시간 API (날짜 미포함). 현장 변경이 즉시 반영되지 않을 수 있음' (data is real-time without a date, and field changes may not be immediately reflected). This informs the agent about potential staleness. However, it does not disclose other behavioral aspects such as authentication requirements, rate limits, or response shape (though the output schema exists). The behavior is partially transparent, deserving a middle score.

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 well-structured and front-loaded with the primary purpose, followed by the facility list, the parameter explanation, and a caveat. It is not long, though the inclusion of full English and Japanese translations adds some verbosity. Each section adds valuepurpose, parameter, caveat), and the format is easy to parse. It earns a 4 for being appropriately concise without sacrificing necessary detail.

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 has a single parameter, an output schema (signal indicates has output schema: true and the description explains the parameter semantics and a data-freshness caveat, it is reasonably complete for an agent to call it correctly. The lack of usage guidance is a minor gap, but the core invocation are covered. The description is adequate for a simple lookup tool, though it could improve by mentioning the response structure or typical use cases, but these are partially covered by the output schema.

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 has 0% description coverage for the only parameter 'station_name', but the description compensates by explicitly stating 'station_name: 역 이름 부분일치 (예: ‘서울’, ‘부산’)' — explaining that the station name is matched as a partial string and providing concrete examples. This adds meaning beyond the type definition and helps the agent understand acceptable input. It is not exhaustive (e.g., case sensitivity or language nuances are missing but it significantly understanding, warranting a 4.

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 tool's purpose: '역 이름으로 편의시설 정보 조회' (look up facility information by station name) and explicitly lists the facility categories (elevator, escalator, restroom, nursing room, information center). It is specific about the verb and resource, and mentions it is a real-time API. However, it does not explicitly distinguish itself from sibling tools like get_accessible_facilities or get_station_facilities_detail, so it falls short of a 5.

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 no guidance on when to use this tool versus alternatives. It does not mention any prerequisites, conditions, or exclusions. There is no reference to sibling tools or differing use cases. An agent cannot discern from the description whether to choose this over get_accessible_facilities or list_stations_with_elevator for a particular query.

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