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

Annotations already declare readOnly/idempotent/non-destructive, so the safety profile is covered. The description adds genuinely new behavioral facts beyond them: a valid Key is required, anonymous access is refused, and the default window is the last 30 days when from/to are omitted.

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?

Front-loads the aggregate and its metrics, then parameters, then usage trigger, then auth requirement. Three compact clauses with no filler; every sentence contributes information the agent needs.

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?

With no output schema, the description compensates by listing the returned metrics and the daily curve. Auth, defaults, and required fields are all stated. It is complete enough to invoke correctly, with only the slug identifier's exact form unspecified.

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 0%, so the description must carry all parameter meaning and largely does: slug is required, from/to are ISO timestamps, and the default range is 30 days. It leaves ambiguous what slug actually identifies (job id vs. name), which is a minor residual gap.

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?

Names a specific resource (岗位) and operation (一段时间汇总) and enumerates the exact metrics returned: 会话数、真人对话轮数、埋点数、动作调用数、tokens、按日曲线. This clearly separates it from siblings like get_session_log or list_sessions, which return records rather than aggregates.

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?

Gives an explicit trigger ('用户问这岗位最近怎么样/今天多少人来就用它') plus a negative instruction not to infer numbers from chat history, which steers the agent away from a plausible wrong behavior. It does not name an alternative tool for adjacent needs, so it stops short of a full when/when-not/alternatives statement.

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