get_hk_operation_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 the return format ('Markdown格式的运营能力数据表格或错误信息' - Markdown-formatted operational capability data table or error message), which is helpful. However, it doesn't disclose critical behavioral traits such as whether this is a read-only operation, potential rate limits, authentication requirements, data freshness, or what happens with invalid inputs beyond generic error messages. For a data-fetching tool with zero annotation coverage, this leaves significant gaps.

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 well-structured. It starts with the purpose, then lists parameters with explanations and examples, and ends with the return format. Each sentence earns its place by providing essential information without redundancy. However, it could be slightly more front-loaded by emphasizing the tool's uniqueness relative to siblings, but overall it's efficient and clear.

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 complexity (3 required parameters, no annotations, but with an output schema), the description is moderately complete. It covers the purpose, parameters, and return format, which is adequate for basic use. However, it lacks details on behavioral aspects (e.g., error handling, data sources) and doesn't differentiate from sibling tools, which reduces completeness. The presence of an output schema means the description doesn't need to explain return values in depth, but other gaps remain.

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 substantial meaning beyond the input schema, which has 0% description coverage. It explains each parameter: 'code' as '港股代码 (如 'hk.00700')' (Hong Kong stock code, e.g., 'hk.00700'), 'year' as '4位年份 (如 '2023')' (4-digit year, e.g., '2023'), and 'quarter' as '季度 (1, 2, 3, 或 4)' (quarter: 1, 2, 3, or 4). This provides clear examples and constraints (e.g., quarter values), compensating well for the lack of schema descriptions. Since there are 3 parameters and the description covers them all, it merits a high score.

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: '获取港股季度运营能力数据 (如周转率等)' which translates to 'Get Hong Kong stock quarterly operational capability data (such as turnover rates, etc.)'. It specifies the verb ('获取' - get), resource ('港股季度运营能力数据' - Hong Kong stock quarterly operational capability data), and provides examples ('如周转率等' - such as turnover rates). However, it doesn't explicitly distinguish itself from sibling tools like 'get_operation_data' or 'get_hk_balance_data', which is why it doesn't achieve a perfect score.

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. With many sibling tools available (e.g., 'get_hk_balance_data', 'get_hk_profit_data', 'get_operation_data'), there's no indication of what makes this tool distinct or when it should be chosen over others. The only implicit context is that it's for Hong Kong stocks and quarterly data, but this doesn't help differentiate it from similar tools.

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