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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is covered. The description adds the aggregation semantics ('Totals for the window, by account'), clarifying this is a rolled-up summary rather than a per-day series, which the schema does not state.

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 sentences, front-loaded with what the tool returns, followed by sibling routing. No wasted text.

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?

Complete enough for a read-only stats tool: it states the metrics and aggregation level, and annotations carry the safety profile. Without an output schema, it could hint at the response shape, a minor gap.

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 range and linkedAccountId parameters are fully documented in the schema. The description adds no format or syntax detail beyond referencing the date range, so the baseline 3 is appropriate.

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?

States a specific verb and resource plus the exact metrics returned (send volumes, acceptance and reply rates) for one LinkedIn account over a date range. It also names what it is not, distinguishing it from `analytics_campaign` and `linkedin_account_daily_stats`.

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?

Explicitly routes the agent: use `analytics_campaign` for a single campaign and `linkedin_account_daily_stats` for a day-by-day breakdown. This covers both when-to-use and named alternatives with conditions.

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