机构研究与评级查询（同花顺问财）

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

No annotations are present, so the description carries the full transparency burden. It discloses that input is a natural-language question and cites the data source, but it does not state read-only behavior, response format, pagination behavior, limits, or error characteristics. These are meaningful gaps for a query tool.

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 compact and front-loaded: it lists the data scope first, then input mode, then source. All three sentences contribute useful information with no filler. It earns a 4 rather than 5 because it partially repeats the title's scope and does not add structure like usage examples.

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 simplicity (one required parameter, no nested objects), the description is minimally viable: an agent can invoke it with a natural-language query and understand the topic area. However, the absence of output schema, pagination guidance, and sibling differentiation leaves notable gaps, especially among many overlapping query_* tools.

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 documents all three parameters. The description only reinforces that the query is a natural-language sentence, adding no new semantic detail about page, limit, or query formatting. Baseline 3 applies.

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 specifies a clear action ('查询') and a detailed resource scope: research report ratings, earnings forecasts, ESG, credit ratings, issuer ratings, fund ratings, and broker gold stocks. This makes the tool's purpose identifiable. However, it does not explicitly distinguish itself from sibling tools like query_fund_data or search_reports, so it falls short of a 5.

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 gives no guidance on when to use this tool versus the many sibling query/search tools. It does not mention alternatives, exclusions, or conditions. The natural-language input and data source are context, but not usage direction.

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