search_hk_stocks

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格式的搜索结果') but lacks critical behavioral details: whether this is a read-only operation, if it requires authentication, rate limits, error handling, or how results are structured (e.g., pagination). For a search 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 concise and well-structured: a brief purpose statement followed by Args and Returns sections. Every sentence adds value without redundancy. It could be slightly more front-loaded by emphasizing the tool's scope earlier, but overall it's 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 low complexity (one parameter) and the presence of an output schema (which handles return values), the description is minimally adequate. However, with no annotations and incomplete parameter guidance, it leaves gaps in behavioral transparency and usage context. It's complete enough for basic use but lacks depth.

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 minimal semantics: it explains 'keyword' as '搜索关键词 (股票名称或代码)' (search keyword: stock name or code), which clarifies the parameter's purpose. However, schema description coverage is 0%, and the description doesn't compensate fully—it lacks details on keyword format, length limits, or examples. With one parameter and some added meaning, it meets the baseline.

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: '搜索港股股票' (search Hong Kong stocks). It specifies the verb '搜索' (search) and resource '港股股票' (Hong Kong stocks), making the intent unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'search_us_stocks' or 'get_popular_hk_stocks', which would be needed for 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. It doesn't mention sibling tools like 'search_us_stocks' for US stocks or 'get_popular_hk_stocks' for trending stocks, nor does it specify use cases or prerequisites. The agent must infer usage from the tool name alone.

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