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

With no annotations, the description carries the full burden. It communicates this is a read-style lookup ('조회합니다' — queries), defines input limits (maximum 100), and enumerates expected statuses (계속사업자, 휴업자, 폐업자 등). It does not mention error handling or network dependencies, but for a simple query tool the behavioral disclosure is adequate and non-misleading.

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 compact, front-loaded with the core purpose, and then organized clearly into Args and Returns sections. Every line adds value: input format, example, limit, and expected output statuses. No redundant or vague wording is present.

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 single-parameter lookup tool, the description covers everything needed to invoke it correctly: the meaning of the parameter, its format constraints, the batch limit, and the kind of result returned. Since an output schema reportedly exists, the description appropriately does not need to detail the full return structure.

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 schema provides no description coverage for business_numbers, but the description fully compensates: it identifies the parameter, gives a concrete example, requires 10-digit numeric strings without hyphens, and sets a maximum of 100 items. This is exactly the kind of semantic detail an agent needs beyond the raw array-of-strings 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 states a specific action and resource: '사업자등록번호로 사업 상태를 조회합니다' (queries business status by business registration number). This clearly distinguishes it from sibling tools like get_air_quality or get_weather_forecast, which cover entirely different domains.

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 makes the use case obvious: when a caller has a Korean business registration number and wants to know the business status. It also gives concrete input constraints (10 digits, no hyphens, max 100 numbers), giving clear context. It does not explicitly name alternatives, but the sibling tools are unrelated, so no exclusion is necessary.

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