scan_market

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds context that filtering is done server-side and results are sorted, which is useful. It does not mention pagination behavior, potential delays, or result format limitations.

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, information-dense sentence that leads with the tool's name and core purpose. It avoids redundancy and wasted words while covering the essential functionality.

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 complexity of 11 parameters and no output schema, the description gives a solid high-level overview (filter and sort) but omits specifics like return fields, pagination via limit, or result example. It is adequate but leaves the agent to infer details from parameter names.

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 each of the 11 parameters having a clear description. The tool description only lists generic filter categories (涨跌幅、成交量、换手率、市盈率), which the schema already details. No additional syntax or usage nuance is provided 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 explicitly states the tool performs conditional stock screening ('条件选股'), fetches full-market A-share quotes, filters server-side, and returns sorted results. This clearly differentiates it from sibling tools like get_all_a_share_quotes, which fetch data without filtering.

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 conveys a clear use case: selecting stocks by combining filters such as price change, volume, turnover rate, and P/E ratio. It implies this tool is for screening, not simple quote retrieval. However, it does not explicitly name alternative tools or state when not to use it.

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