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

Annotations only include openWorldHint, so the description carries most of the behavioral disclosure burden. It states that the tool queries per-enterprise periodic changes, specifies the exact indicator categories, and explicitly lists what it does not cover. The use of '查询' clearly implies a read-style operation, and no contradiction exists with the annotation.

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 purpose, followed by inclusions, exclusions, and examples. The embedded Pricing block adds non-semantic clutter, but the main content is organized and each section earns its place. It is somewhat verbose but not wasteful.

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 output schema exists and annotations are minimal, the description sufficiently covers purpose, scope, exclusions, and typical usage. It also differentiates from similarly named siblings like enterprise_change_capital_brand_recognition and enterprise_change_capital_brand_innovation. It does not discuss result format, but that is addressed by the output schema.

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 parameters with examples, so the baseline is 3. The description adds value by framing the parameters in a query context, showing combined real-world questions like '中国比亚迪股份有限公司按时披露' and clarifying that the query is per specific company rather than batch/industrial-chain screening.

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 clearly states it queries periodic changes in capital-brand transparency by specific company name ('基于具体企业名称，按企业查询资本品牌方面的周期变化') and enumerates covered indicators: disclosure timeliness, accuracy, truthfulness, media scrutiny, and regulatory inquiry/penalties. It also explicitly excludes institutional-holding/recognition metrics, distinguishing it from adjacent 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 provides explicit inclusion boundaries and exclusions: it is for disclosure and regulatory-risk signals, and says '不用于机构持股等资本市场认同度指标' and '不包含：非本分类指标；按园区/产业链批量筛企业名单'. Typical question formats ('典型问法') further clarify when and how to use it. This is strong usage guidance even though no alternative tool is named.

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