财务数据查询（同花顺问财）

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

With no annotations, the description carries the full burden. It usefully discloses that data comes from an external source (同花顺问财) and that input should be a natural-language question. However, it does not mention return format, pagination behavior, potential rate limits, or the fact that the query may be rewritten into a standard financial question.

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 two concise sentences with no filler: the main purpose is front-loaded and the data source is appended in a separate line. Every phrase contributes useful information.

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?

Because there is no output schema and no annotations, the description should explain what the tool returns or how results are presented, but it only states what is queried and the data source. It also does not provide an example query or clarify pagination behavior, leaving the agent under-informed for a real external data-query 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?

Schema description coverage is 100%, so page, limit, and query are already documented in the input schema. The tool description adds no parameter-specific meaning beyond restating natural-language input, which the schema already covers. Thus the baseline 3 is appropriate.

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 specific verb (查询) and a specific resource (全市场个股财务指标), and lists concrete example indicators such as 营业收入, 净利润, ROE, 负债率, and 现金流. This clearly differentiates it from sibling query_* tools that target market, industry, macro, index, fund, or futures 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 usage by saying natural-language questions are accepted and giving example metric categories, so an agent can infer when to invoke it. However, it does not explicitly name alternatives or state when not to use this tool, leaving the agent to guess among the many query_* and select_* siblings.

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