公司经营数据查询（同花顺问财）

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It does disclose the external data source (同花顺问财) and the natural-language input style, which is useful. But it does not mention output shape, pagination behavior, error handling, or whether the query is executed live against the external service.

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 three short sentences, each with a clear purpose: scope, input format, and data source. There is no filler or redundant phrasing, and the most identifying information is front-loaded.

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 description is adequate for a simple one-required-param tool with clearly listed data domains. However, there is no output schema and no annotations, and the description does not cover what the result looks like, whether pagination applies to the natural-language query results, or how to handle ambiguous queries. It also relies on the reader to infer how this differs from nearby siblings.

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%, so the schema already explains all three parameters. The description adds only a redundant restatement of the natural-language input requirement and does not provide any deeper meaning about page or limit beyond what the schema already states.

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 states a clear verb+resource: query business operating data, and enumerates concrete categories (主营业务构成、主要客户、供应商、参控股公司、股权投资、重大合同). It is fairly distinguishable from siblings like query_market_data or query_finance_data, though it could more explicitly separate itself from query_management_data and query_basicinfo_data.

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 implies when to use the tool: when business operating data such as major clients, suppliers, or equity investments is needed. It also instructs that input should be a natural-language question. However, it gives no explicit guidance about when not to use it or which sibling tools are better alternatives for adjacent data types.

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