事件数据查询（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 behavioral burden. It discloses that the input is natural language and that the data comes from 同花顺问财, and the verb '查询' implies a read-only operation. However, it does not describe return shape, pagination behavior, or what happens when the query is rewritten.

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 sentences with no filler. The first sentence front-loads the core purpose and event types; the second adds the data source and input mode. Every sentence earns its place.

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 distinguishes the tool well among many siblings and covers the core input behavior, but without an output schema or annotations it should ideally say more about what the agent can expect in the result and how pagination works. The gaps are not fatal, but they are noticeable for a tool backed by an external data source.

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 baseline is 3. The description reinforces the meaning of 'query' by stating that it is a natural-language question, but it adds no additional semantic context for 'page' or 'limit' beyond what the schema already provides.

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 names a specific verb ('查询') and a specific resource ('个股...事件数据') with concrete examples such as 业绩预告、增发、质押、解禁、调研、监管函. This clearly distinguishes it from sibling tools like query_market_data and query_finance_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 makes clear that this tool is for event data expressed as natural-language questions, which gives the agent strong situational context. It does not explicitly name alternatives or say when not to use it, but the boundary is reasonably clear from the event-data examples.

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