stock_gdfx_holding_change_em

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds that it returns a pandas DataFrame of top 10 circulating shareholders, which is useful. However, it does not disclose data scope (e.g., all stocks vs. a single stock), pagination, or error behavior, so behavioral context remains thin.

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 logically structured with title, URL, parameter, and return lines. The title line duplicates the annotation title, which is slightly redundant, but the URL and parameter documentation earn their place. It is not overly verbose.

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?

There is no output schema, and the description is too sparse for a shareholder analysis tool. It fails to clarify whether the query is for a single stock or all stocks, what the resulting DataFrame columns represent, or how the date parameter affects the output. Given the complexity and many siblings, the description leaves significant gaps.

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 only provides 'date' as a string with default '20210930'. The description adds that it is the '报告期' (report period), giving essential meaning. While it does not explicitly state the format (e.g., YYYYMMDD), the default strongly implies it. For a single-parameter tool, this is adequate compensation for the 0% schema description coverage.

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 and content: East Money's shareholder holding change statistics for top 10 shareholders, with a specific URL. The title and name align on the main purpose, but there is no explicit verb like 'fetch' or 'query'. A minor inconsistency exists between the title (十大股东) and return (十大流通股东), yet it still distinguishes from siblings like stock_gdfx_holding_analyse_em by emphasizing 'change' statistics.

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 the many sibling shareholder analysis tools. There are no alternatives, exclusions, or prerequisites. The only usage hints are the name and the parameter documentation, so an agent cannot judge when this tool is appropriate.

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