stock_gdfx_holding_analyse_em

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

Annotations already declare this as a read-only, idempotent, non-destructive operation, so the description does not need to repeat that. It adds the return type (pandas DataFrame) and the meaning of the date parameter (报告期/reporting period), which provides some extra context. However, it does not disclose other behavioral details such as pagination, rate limits, or data granularity beyond the annotations.

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 compact and well-structured as a docstring, with a title, URL, parameter description, and return type. Every line serves a purpose, and it is easy to scan. The inclusion of the URL may be redundant but does not detract significantly from conciseness.

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 tool with robust annotations, the description covers the basic purpose and return type but falls short in differentiating from close sibling tools and explaining the date parameter's format or possible values. Without an output schema, it would benefit from describing the DataFrame columns beyond just '十大股东'.

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 0% description coverage for the 'date' parameter, but the description partially compensates with ':param date: 报告期' and ':type date: str', clarifying that date refers to a reporting period. It does not explicitly state the format (YYYYMMDD) or valid values, relying on the schema default example. Thus, it adds basic meaning but lacks depth.

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 tool's function: retrieving top-10 shareholder data from East Money's shareholder analysis section, as indicated by the title and '十大股东' return type. It distinguishes from sibling tools like stock_gdfx_free_holding_analyse_em by specifying '十大股东' (top 10 shareholders) rather than free-float holdings, though it lacks an explicit verb like 'get' or 'list'.

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. With many sibling tools for different holding analyses (e.g., free holding, holding change, holding detail), the lack of differentiation or explicit usage context is a significant gap. The URL merely points to the data source but does not explain selection criteria.

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