stock_gdfx_free_holding_analyse_em

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds the source URL and return type but does not disclose additional behavioral traits such as data scope, pagination, or data freshness. It does not contradict 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 concise and structured as a docstring with source URL, parameter, and return sections. Every line carries information, though a brief summary sentence at the beginning would improve front-loading.

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 has a single parameter and no output schema, so the description should clarify the scope of the returned data. It only states '十大流通股东' without specifying whether this covers all stocks or a particular stock, nor what columns are included. This ambiguity is a significant completeness gap for an agent selecting the tool.

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, so the description must compensate. It does add meaning by documenting 'date' as 报告期 (report period) with type str, but it does not specify the expected format (e.g., YYYYMMDD) or whether any specific date constraints apply. The schema default '20230930' hints at format but is not explained.

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 identifies the resource (股东持股分析-十大流通股东) and return type (pandas.DataFrame of top 10 free shareholders), making the core purpose clear. However, it lacks a strong verb (e.g., 'fetches', 'queries') and does not differentiate from closely related siblings like stock_gdfx_free_top_10_em or stock_gdfx_holding_analyse_em.

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?

No guidance is provided on when to use this tool versus alternatives, nor any exclusions or context for selection. The description merely restates the data source and parameter without explaining use cases or distinguishing from similar tools.

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