get_minority_shareholder_status

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

With no annotations, the description carries the behavioral disclosure burden. It discloses the underlying endpoint (Open DART's 소액주주 현황), the data provided (number of shareholders, share of total shareholders, proportion of shares), and the report types. It does not mention rate limits, auth requirements, or failure modes, but the read-only nature and data semantics are reasonably clear.

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 organized: a one-sentence summary up front, a brief note on the underlying source, then a tight Args block. Every sentence adds value, and the structure makes it easy for an agent to quickly locate parameter requirements.

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?

The description covers all four parameters with formats and examples, describes the endpoint and the semantics of the returned data, and an output schema already exists. There are no significant gaps that would prevent an agent from selecting and invoking this tool correctly.

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 provides only titles and types (0% description coverage), so the description fully compensates by documenting each parameter: an example corp_code, the expected year format, and every report_type value with Korean labels and a default. This is exactly the kind of parameter guidance an agent needs.

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 verb ('Get'), a specific resource ('minority/small shareholder status (소액주주 현황)'), and the temporal scope ('across years'). It clearly distinguishes from sibling tools like get_major_shareholder_status by focusing on the minority/small shareholder perspective.

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 clearly implies when to use this tool: whenever minority shareholder status data is needed, and it explains what the tool reports. It does not explicitly name alternatives or state when not to use it, but the sibling list and subject matter make the primary use case unambiguous.

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