kosis_meta

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

Beyond the readOnlyHint annotation, the description discloses specific error behaviors (err 20/21 vs. err 30), what kinds are not supported (NCD, OBJ, CLS), and that axes are automatically handled by kosis_data. This adds meaningful behavioral context.

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 dense but well-organized, front-loading the main purpose then listing crucial warnings. Each sentence contributes actionable information, and the use of emojis aids scannability without adding 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?

For a metadata-lookup tool with no output schema, the description covers all essential context: what it returns, relationship to sibling tools, error semantics, and limitations. It is complete enough for an agent to decide when and how to use it.

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 description explains the 'kind' parameter and its accepted values (from kosis_guide) and its default, but does not elaborate on org_id or tbl_id. Since these are self-explanatory in context and the schema covers them implicitly, the description adds moderate semantic value beyond the raw schema.

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 that the tool retrieves metadata (items, periods, sources, comments) for a statistical table, distinguishing it from data retrieval. It is specific about the resource and the scope of information provided.

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?

Explicitly instructs to call this tool before kosis_data to check ITM and PRD to avoid errors 20/21, and warns about the absence of classification-axis kinds and the error behavior of unknown kinds. It also points to kosis_guide for possible kind values, providing clear when-to-use and when-not-to-use guidance.

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