查询报名汇总

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

Annotations already provide readOnlyHint, idempotentHint, and destructiveHint, so the description doesn't need to repeat those. It adds meaningful behavioral constraints beyond annotations: the output is aggregate-only and explicitly excludes names, phone numbers, emails, and WeChat IDs.

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?

Two short sentences with no wasted words: the first states what statistics are returned, and the second sets the privacy boundary. Information is front-loaded and schema details are not repeated.

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 covers the scope and privacy characteristics well, but it doesn't state the default behavior when both optional date parameters are omitted, and with no output schema, the exact response structure is left unspecified. Overall it is adequate but has minor gaps.

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%, with both dateFrom and dateTo clearly described as inclusive/exclusive ISO-8601 timestamps. The tool description adds no further parameter detail, which is acceptable since the schema already carries the semantic load.

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 resource ('报名汇总'), and enumerates the exact statistic families returned: cumulative, today, last hour, main forum, and data quality. It also clarifies aggregate-only output, which differentiates it from sibling distribution 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?

Usage context is implied by '只返回聚合数据' — the agent can infer this tool is for aggregate registration statistics, not raw records or distributions. However, no explicit when-to-use guidance or alternatives are named, so selection relies on inference.

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