get_hk_profit_data

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that the tool returns 'Markdown格式的盈利能力数据表格或错误信息' (Markdown-formatted profitability data table or error message), which adds some context about output format and error handling. However, it lacks details on permissions, rate limits, data freshness, or whether this is a read-only operation (though 'get' implies reading). For a tool with zero annotation coverage, this is insufficient.

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 appropriately sized and front-loaded, with the purpose stated first, followed by parameter details and return information. Every sentence adds value: the first defines the tool, and the subsequent lines explain inputs and outputs. It could be slightly more concise by integrating the parameter explanations more tightly, but it avoids unnecessary verbosity.

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's moderate complexity (3 parameters, no annotations, but with an output schema), the description is reasonably complete. It explains the purpose, parameters, and return format. Since an output schema exists, the description doesn't need to detail return values extensively. However, it could improve by adding more behavioral context (e.g., data sources, limitations) to compensate for the lack of annotations.

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 adds significant meaning beyond the input schema, which has 0% description coverage. It explains that 'code' is a '港股代码 (如 'hk.00700')' (Hong Kong stock code, e.g., 'hk.00700'), 'year' is a '4位年份 (如 '2023')' (4-digit year, e.g., '2023'), and 'quarter' is '季度 (1, 2, 3, 或 4)' (quarter: 1, 2, 3, or 4). This clarifies the semantics, formats, and constraints for all three parameters, fully compensating for the schema's lack of descriptions.

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 tool's purpose as '获取港股季度盈利能力数据 (如ROE、净利润率等)', which translates to 'Get Hong Kong stock quarterly profitability data (such as ROE, net profit margin, etc.)'. This specifies the verb ('get'), resource ('Hong Kong stock profitability data'), and scope ('quarterly'), making the purpose clear. However, it doesn't explicitly distinguish this tool from sibling tools like 'get_profit_data' or 'get_hk_balance_data', which might handle different data types or markets.

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 no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_profit_data' (which might be for non-HK stocks) or 'get_hk_balance_data' (for balance sheet data), nor does it specify prerequisites or exclusions. Usage is implied only by the tool's name and description, with no explicit context for selection.

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