stock_gpzy_pledge_ratio_em

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is known. The description adds only the data source URL and return type (pandas.DataFrame), but no additional behavioral context such as pagination, rate limits, or the meaning of the returned data. It does not contradict annotations, but it also provides little beyond them.

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 short and uses a standard docstring format, front-loading the source and return type. However, it repeats the URL twice (in the description and the param doc), which is minor redundancy. Overall it is appropriately sized and gets to the point quickly.

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 tool with one parameter, the description provides the essential source, param meaning, and return type. It does not explain the output columns, whether the data is per-company or aggregate, or any relationship to the detail variants. Given the lack of an output schema, slightly more detail about the returned DataFrame would improve completeness.

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 has one parameter (date) with no description, and schema coverage is 0%. The description compensates by explaining that date is a specified trading day and points to the URL for valid values, along with the default format evident from the schema's default value '20240906'. This adds meaningful context beyond the bare 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 clearly states that this tool provides the pledge ratio for listed companies from Eastmoney, with a specific URL and data domain. It identifies the resource (上市公司质押比例) and the verb is implicit in the function name. However, it does not explicitly differentiate itself from sibling tools like stock_gpzy_pledge_ratio_detail_em, which is a detail variant, so it's not fully distinct.

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 gives no guidance on when to use this tool versus alternatives. It only mentions that the date parameter can be queried by visiting the URL. There is no comparison to the many related stock_gpzy_* tools or any exclusions for when this tool should be preferred.

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