get_us_quotes

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint: true, and the description is consistent ('获取' means 'get'). It adds return field info (latest price, change %, volume) but lacks deeper behavioral details like rate limits or error handling. With annotations present, the score is moderate.

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 in Chinese that directly states the tool's action and return values. No fluff or redundancy; every word adds value.

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?

The tool is simple with one parameter, but the description lacks usage context and sibling differentiation. It doesn't mention that it's for specific codes (though the schema implies it) or contrast with historical or all-market quote tools. Reasonably complete for a basic quote tool 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 coverage is 100%, with the 'codes' parameter described as '美股代码数组，如 ["AAPL", "BABA"]'. The tool description does not add extra meaning beyond the schema, so baseline 3 is appropriate.

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 gets US stock real-time quotes and lists return fields (latest price, change %, volume). However, it doesn't explicitly differentiate from sibling tools like get_all_us_quotes or get_us_history_kline, so it's clear but not fully distinguishing.

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 such as get_all_us_quotes or get_hk_quotes. No exclusions, alternatives, or context are mentioned, leaving usage decisions to the agent's inference.

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