get_hk_growth_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 states the tool returns 'Markdown格式的成长能力数据表格或错误信息' (Markdown-formatted growth data table or error message), which is useful. However, it doesn't disclose other behavioral traits: whether it's read-only (implied but not explicit), rate limits, authentication needs, data freshness, or what constitutes valid inputs beyond the basic schema. 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 front-loaded: the first line states the purpose, followed by clear sections for Args and Returns. Every sentence earns its place, with no redundant information. However, the structure could be slightly improved by integrating the parameter details more seamlessly, but it remains efficient.

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 required parameters, no annotations, but has an output schema), the description is partially complete. It covers the purpose, parameters, and return format, but lacks usage guidelines, behavioral context (e.g., error handling, data sources), and differentiation from siblings. The output schema existence means the description needn't detail return values, 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?

Schema description coverage is 0%, so the description must compensate. It adds meaningful semantics for all three parameters: '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 clarifies format and constraints beyond the bare schema, though it doesn't explain edge cases (e.g., invalid codes).

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: '获取港股季度成长能力数据 (如同比增长率等)' which translates to 'Get Hong Kong stock quarterly growth capability data (such as year-over-year growth rates, etc.)'. It specifies the verb ('获取' - get), resource ('港股季度成长能力数据' - Hong Kong stock quarterly growth data), and scope ('港股' - Hong Kong stocks). However, it doesn't explicitly distinguish from siblings like 'get_growth_data' (which appears to be for non-HK stocks) or 'get_hk_profit_data' (which focuses on profit rather than growth).

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_growth_data' (for non-HK stocks) or 'get_hk_profit_data' (for profit data), nor does it specify prerequisites, exclusions, or contextual triggers. The agent must infer usage from the tool name and description alone.

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