숭실대학교 중앙도서관의 현재 좌석 현황을 층별로 조회합니다. 응답에는 해당 층의 전체/이용 가능/예약/사용 불가 좌석 수와 구역별 분포가 포함됩니다. compact=true 지원. 좌석 집계는 공개 정보이며 인증이 필요하지 않습니다. 이 도구는 읽기 전용이며, 좌석 예약은 별도의 동작 도구로 분리되어 있습니다.
| Name | Required | Description | Default |
|---|---|---|---|
| floor | Yes | 조회할 도서관 층 코드. 가능한 값: 2 (2층), 5 (5층), 6 (6층). | |
| compact | No | compact=true: 전체/가용/예약 수치만 반환 (층 요약). compact=false(기본): 구역별 상세 포함. |
Changes observed during successful MCP inspections.
Input schema / properties / mcp_session_idRemoved value: -{
- "description": "start_auth(LIBRARY)로 발급받은 MCP session ID. 없거나 LIBRARY 미연동이면 loginUrl과 함께 AUTH_REQUIRED를 반환.",
- "type": "string"
-}Input schema / requiredPrevious value: -[
- "floor",
- "mcp_session_id"
-]New value: +[
+ "floor"
+]Input schema / properties / mcp_session_id / descriptionPrevious value: -"MCP session ID issued by start_auth(LIBRARY). If absent or LIBRARY not linked, returns AUTH_REQUIRED with a loginUrl."New value: +"start_auth(LIBRARY)로 발급받은 MCP session ID. 없거나 LIBRARY 미연동이면 loginUrl과 함께 AUTH_REQUIRED를 반환."Input schema / properties / compactAdded value: +{
+ "description": "compact=true: 전체/가용/예약 수치만 반환 (층 요약). compact=false(기본): 구역별 상세 포함.",
+ "type": "boolean"
+}Input schema / properties / mcp_session_idAdded value: +{
+ "description": "MCP session ID issued by start_auth(LIBRARY). If absent or LIBRARY not linked, returns AUTH_REQUIRED with a loginUrl.",
+ "type": "string"
+}Input schema / requiredPrevious value: -[
- "floor"
-]New value: +[
+ "floor",
+ "mcp_session_id"
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnlyHint and destructiveHint annotations, the description adds meaningful behavioral context: the seat aggregation is public, authentication is not required, the tool is read-only, and reservation is out of scope. It also describes the response contents, which helps an agent understand what to expect. No contradiction with annotations.
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: purpose first, then response contents, then compact behavior, then auth and reservation notes. It is concise, though the read-only note and compact=true support partly repeat what annotations and schema already provide.
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?
For a simple read-only status lookup with no output schema, the description provides enough: it explains what the response includes, states that no authentication is required, and clarifies scope. Combined with the 100% schema coverage, an agent can select and invoke the tool correctly without missing critical information.
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?
Schema description coverage is 100%, and the schema already documents the floor values and the compact parameter behavior. The description only repeats that compact=true is supported without adding meaning beyond the schema, so the baseline score applies.
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 identifies the operation: retrieving current library seat status by floor, and specifies the response contents (total/available/reserved/unavailable counts and area distribution). It is clear and specific, but it does not explicitly differentiate from sibling tools such as get_library_available_seats or recommend_library_seats.
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 gives useful usage context: the data is public, no authentication is needed, the tool is read-only, and seat reservation is intentionally kept in separate action tools. It does not name the specific alternative tools, but it does provide an explicit exclusion for reservation-related tasks.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.