板块基本面：获取概念或行业板块的PE、ROE、毛利率、财务经营数据等基本面数据

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes the tool as a data retrieval operation ('获取' - get), implying it is likely read-only and non-destructive, but does not confirm this or address other behavioral aspects such as rate limits, authentication needs, error handling, or data freshness. The description adds minimal context beyond the basic operation.

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 a single, concise sentence that front-loads the purpose. However, it is repetitive with the title and could be more structured by separating key points (e.g., data types, usage context). It avoids waste but lacks elaboration that might aid clarity.

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?

Given the tool's moderate complexity (2 parameters, fundamental data retrieval), the description is reasonably complete. It outlines the data types returned (PE, ROE, etc.), and with an output schema present, detailed return value explanations are not needed. However, it could improve by addressing behavioral aspects (e.g., data sources, update frequency) since annotations are absent.

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?

Schema description coverage is 100%, with clear descriptions for both parameters ('date' and 'query'). The description mentions '概念或行业板块名称' (concept or industry sector name), which aligns with the 'query' parameter, but does not add significant meaning beyond what the schema provides. With high schema coverage, the baseline score of 3 is appropriate as the description compensates minimally.

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?

Tautological: description restates name/title.

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. It does not mention sibling tools like 'sectorCapAnalysis' or 'stockFunAnalysis' (for individual stocks), nor does it specify prerequisites, exclusions, or contextual cues for selection. Usage is implied by the tool's name and description but not explicitly stated.

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