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

With only openWorldHint annotated, the description carries most of the behavioral burden; it uses '查询' to signal a read operation and clarifies the covered/excluded data scopes. However, it does not disclose operational behavior such as result granularity, temporal coverage of the '周期变化', data-source limitations, or any throttling/pagination behavior.

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 front-loaded with the core action and uses labeled sections for indicators, exclusions, and examples, making it scannable. The pricing JSON is metadata rather than prose, and the sections are not redundant, though the example list is slightly longer than strictly necessary.

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?

For a two-parameter query tool with an output schema, the description covers the substantive domain, scope exclusions, and parameter phrasing well. It is missing a bit of operational context such as how far back the '周期变化' reaches or whether results are limited to listed companies, but overall the agent can select and invoke it correctly.

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?

The input schema already covers both required parameters at 100%, so the baseline is 3. The description adds value by showing three typical question forms that map country/company values (e.g., 中国+比亚迪股份有限公司, 美国+Tesla, Inc., 日本+丰田自动车株式会社), helping the agent extract parameters correctly.

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 opens with a specific action and resource: query period changes in capital-brand transparency for a named enterprise, and then itemizes concrete indicators such as timely/accurate/truthful disclosure, media questioning, and regulatory inquiry/penalty. It also explicitly rules out institutional-holding recognition measures, distinguishing it from adjacent capital-brand and recognition-focused sibling tools.

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 explicit intended use ('用于查询信息披露…以及媒体质疑与监管问询处罚') and explicit non-goals ('不用于机构持股…', '不包含：非本分类指标；按园区/产业链批量筛企业名单'). Typical question phrasings further demonstrate how the agent should frame queries.

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