get_hk_cash_flow_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. It mentions the return format ('Markdown格式的现金流数据表格或错误信息' - Markdown-formatted cash flow data table or error message), which is useful. However, it lacks critical behavioral details: whether this is a read-only operation, potential rate limits, data freshness, error conditions beyond invalid inputs, or if it requires specific permissions. 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 well-structured and appropriately sized: a clear purpose statement, followed by Args and Returns sections with bullet-like formatting. Every sentence adds value—no fluff. It could be slightly more front-loaded by moving the return format to the first line, but overall it's efficient and easy to parse.

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 complexity (data retrieval with 3 parameters), no annotations, and an output schema exists (implied by 'Returns'), the description is moderately complete. It covers the purpose and parameters well, and the output schema will handle return values. However, it lacks behavioral context (e.g., read-only nature, error handling) and usage guidelines, which are important for a tool in a crowded sibling set. This makes it adequate but with clear gaps.

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?

Schema description coverage is 0%, so the description must compensate. It adds meaningful semantics: 'code' is explained as '港股代码' (Hong Kong stock code) with an example 'hk.00700', 'year' as '4位年份' (4-digit year) with example '2023', and 'quarter' as '季度' (quarter) with allowed values 1-4. This clarifies the purpose and format of all three parameters beyond the bare schema, though it doesn't detail constraints like code validation or quarter integer range.

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: '获取港股季度现金流数据' (get Hong Kong stock quarterly cash flow data) with specific examples like '经营现金流/营业收入比率' (operating cash flow/revenue ratio). It distinguishes from siblings by specifying '港股' (Hong Kong stocks) and '现金流数据' (cash flow data), differentiating from tools like get_hk_balance_data or get_hk_profit_data. However, it doesn't explicitly contrast with the non-HK sibling get_cash_flow_data, which slightly reduces clarity.

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 when to choose this over get_cash_flow_data (for non-HK stocks) or other HK-specific tools like get_hk_balance_data. There's also no information about prerequisites, such as data availability or authentication needs. Usage is implied by the parameters but not explicitly stated.

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