stock_zh_a_st_em

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

Annotations already declare this as a safe, read-only, idempotent operation, so the bar for additional behavioral disclosure is lower. The description adds that it returns a pandas DataFrame and references the Eastmoney gridlist ST board URL, which provides provenance. However, it does not disclose any further behavioral traits such as column contents, data freshness, or that it is a real-time snapshot.

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 extremely concise: a title, a URL, and return type annotation. Every sentence earns its place, providing the data source, the exact board type, and the return format. There is no fluff or redundant information, making it highly efficient.

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 no-parameter, read-only tool with no output schema, the description is adequate but not complete. It states the source and return type but does not describe what the DataFrame contains (e.g., columns like code, name, change percentage) or whether the data is historical or real-time. Given the many sibling stock tools, a bit more detail about the board's content would help an agent invoke it correctly.

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 tool has zero parameters, so the baseline score is 4. The description does not need to explain parameter semantics, and no parameter information is missing. The empty schema is fully covered by the description's implicit 'no parameters needed' context.

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 identifies the resource: Eastmoney's Shanghai/Shenzhen A-share risk warning board (ST stocks), including the specific URL and return type as a pandas DataFrame. It lacks an explicit verb ('get' or 'list'), but the title and name make the function's purpose clear. It is distinguishable from sibling stock tools by the 'st_board' reference.

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?

There is no guidance on when to use this tool versus alternatives. For example, it does not mention that this is for ST/risk-warning stocks specifically, nor does it point to stock_zh_a_spot_em for regular A-share spot data. The description is purely informational with no usage context or exclusions.

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