get_company_board_shareholdings

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It indicates a read operation ('Obtain') but lacks details on permissions, data freshness, rate limits, or error handling. The description doesn't contradict annotations (none exist), but it fails to provide sufficient behavioral context for safe and effective use by an AI agent.

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 a single, well-structured sentence that efficiently conveys the tool's purpose and key input requirement. It avoids redundancy and is front-loaded with essential information, making it easy to parse quickly without unnecessary elaboration.

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 tool has an output schema (which likely defines return values), the description's focus on purpose and input is appropriate. However, with no annotations and low schema coverage, it lacks behavioral and parametric details that would enhance completeness. The description is adequate for basic understanding but insufficient for robust agent decision-making without additional context.

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 description coverage is 0%, so the description must compensate. It adds meaning by specifying that the 'code' parameter is a 'stock code' for a 'listed company', which clarifies the parameter's purpose beyond the schema's generic 'Code' title. However, it doesn't detail format constraints (e.g., length, allowed characters) or provide examples, leaving some ambiguity.

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 the action ('Obtain') and target resource ('board members' shareholding details for a listed company'), making the purpose evident. It specifies the input parameter ('based on its stock code'), which helps understand the scope. However, it doesn't explicitly differentiate from similar sibling tools like 'get_company_board_info' or 'get_public_company_board_shareholdings', which would require more specific distinction.

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 provides minimal usage guidance by implying the tool is for listed companies and requires a stock code, but it doesn't specify when to use this tool versus alternatives (e.g., 'get_company_board_info' for general board info or 'get_public_company_board_shareholdings' for public companies). No explicit exclusions or prerequisites are mentioned, leaving gaps in contextual application.

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