get_fundamentals

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 only lists data fields and does not explain whether the tool returns historical or current values, how missing or invalid codes are handled, or what the output structure looks like. '获取' implies a read, but the description lacks meaningful behavioral context.

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 a single, front-loaded sentence that immediately states the tool's purpose and lists example metrics. It contains no wasted words and is appropriately compact for a one-parameter tool.

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?

For a simple one-parameter fundamental data getter, the description gives a minimum viable picture by naming key fields, but it does not explain the return format or possible time-series behavior. Since there is no output schema, the description should provide more detail about what the agent can expect in the response.

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 schema fully describes the single required parameter 'code' with an example ('600519'), so the description does not need to add parameter details. This hits the baseline of 3 for full schema coverage; the description itself adds no specific parameter semantics beyond the schema.

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 uses a specific verb ('获取') and clearly identifies the resource ('A股基本面数据') with concrete examples of the metrics returned. This effectively distinguishes it from sibling tools like get_kline, get_technical_indicators, and get_realtime_quote, which target market, technical, or price data.

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 implies that this tool is for fundamental data rather than real-time quotes or technical indicators, but it does not explicitly state when to use it or when to choose alternatives. There is no direct comparison to sibling tools or exclusion criteria, so guidance is only implicit.

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