get_us_stock_basic_info

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格式的基本信息表格' - Markdown format basic information table), which adds some behavioral context. However, it lacks critical details: whether this is a read-only operation, potential rate limits, authentication needs, error handling, or what happens with invalid codes. For a tool with zero annotation coverage, this is a significant gap.

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 purpose is stated first, followed by Args and Returns sections. Every sentence earns its place by clarifying parameters and output. It could be slightly more concise by integrating the example directly, but overall it's efficient with zero waste.

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 (2 parameters, 1 required), no annotations, and an output schema exists (implied by 'Returns'), the description is minimally adequate. It covers purpose, parameters, and output format, but lacks usage guidelines, behavioral details like error cases, and doesn't leverage sibling context. With output schema handling return values, the description meets basic needs but has 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 schema provides no parameter details. The description compensates well: it explains 'code' as '美股代码' (US stock code) with an example ('us.AAPL'), and 'fields' as '可选的字段列表' (optional field list). This adds meaningful semantics beyond the bare schema. However, it doesn't specify possible field values or formats, preventing a perfect 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: '获取美股基本信息' (Get US stock basic information). It specifies the verb '获取' (get) and resource '美股基本信息' (US stock basic information), making it distinct from siblings like 'get_us_stock_realtime_data' or 'get_us_historical_k_data'. However, it doesn't explicitly differentiate from 'get_stock_basic_info' (which might be for other markets), so it's not a perfect 5.

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_us_stock_realtime_data' for real-time data or 'get_stock_basic_info' for other markets. There's no context about prerequisites, such as needing a valid stock code, or exclusions. The minimal guidance is insufficient for an agent to make informed choices.

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