get_table_metadata

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

No annotations are provided, so the description carries the full burden. It implies a read-only metadata query (no destructive actions) but does not explicitly state behavior such as idempotency, authentication requirements, or rate limits. The example and return structure give some transparency, but the lack of explicit behavioral disclosure prevents a higher 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 relatively compact, with a clear front-loaded purpose sentence followed by usage context, specific parameter explanations, and an example. The return structure is detailed but relevant. It could be slightly more concise by omitting the explicit return JSON if the output schema is sufficient, but it still earns its place.

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 lack of annotations and the presence of an output schema, the description covers the essential aspects: purpose, usage context, parameters, return values, and an example. It does not address error cases or limitations, but for a metadata query tool with an output schema, it is reasonably 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 has 0% description coverage, but the tool description's Args section fully explains both parameters: org_id as '기관 ID (예: "101")' and tbl_id as '테이블 ID (예: "DT_1B040A3")'. This provides clear semantics beyond the schema, satisfying the need for parameter documentation.

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 '통계표의 메타데이터(구조 정보)를 조회합니다' (queries metadata of statistical tables) and elaborates on the specific structural information (분류항목, 항목, 기간 정보). It differentiates from sibling tools like get_statistics_data by focusing on pre-query metadata inspection.

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 explicitly says '데이터 조회 전에 어떤 필터가 가능한지 확인하는 데 유용합니다' (useful for checking available filters before querying data), indicating when to use it. However, it does not explicitly state when not to use or mention alternative tools, so it loses one point.

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