stock_gdfx_top_10_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 the output type (DataFrame) and a source URL, but discloses no additional behavioral traits such as pagination, rate limits, or data freshness. This is acceptable given the strong annotations but not exemplary.

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 docstring is compact and structured with title, URL, parameters, and return type. It is not overly verbose, though the URL may be extraneous for an AI agent and the title largely repeats the tool name.

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?

With no output schema, the description only vaguely specifies 'top 10 shareholders' and a DataFrame, lacking column details. Given the large family of shareholder-related sibling tools, it does not provide enough context to fully understand the result structure or select the correct 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 no parameter descriptions (0% coverage), but the description defines symbol as 'stock code with market identifier' and date as 'reporting period', providing essential meaning beyond bare types and defaults. It compensates for the schema gap, though it could be more explicit about formats.

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 indicates it retrieves top 10 shareholders from Eastmoney for an individual stock, with return type pandas DataFrame. However, it does not explicitly distinguish itself from sibling tools like stock_gdfx_free_top_10_em, which could lead to confusion.

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, no exclusions, and no situational context. It only lists parameters and return type, leaving the agent without direction for tool selection.

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