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

Annotations already establish read-only, idempotent, non-destructive behavior, so the description adds context a schema cannot: the data reported is actual sent volume, not configured ceilings. That framing ('it is the evidence for whether there is headroom') tells the agent why the call is safe and what it proves. It does not describe aggregation default behavior when `linkedAccountId` is omitted, though the schema covers that.

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?

Three short sentences, front-loaded with what the tool returns, then when to use it, then how it differs from the two adjacent tools. No filler and no repetition of the schema.

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 carries the burden of saying what comes back; 'day-by-day action counts' plus 'reports what was sent' covers the essentials. The exact breakdown of action types per day is not stated, a minor gap for an analytics read with three optional params.

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 all three parameters documented including the accept-both-formats date types and the omit-to-aggregate behavior. The description adds no parameter-level detail beyond that, so baseline 3 applies.

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 names a specific resource and granularity (day-by-day action counts for a LinkedIn account) and explicitly separates itself from two siblings: `linkedin_account_get` (ceilings) and `linkedin_account_update` (limit changes). It does not distinguish itself from `linkedin_account_stats`, the closest sibling, leaving that ambiguity unresolved.

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?

States an explicit trigger ('check how close an account is running to its daily ceilings before raising limits') and names the downstream tool whose call it should precede. It gives clear positive usage context but does not state when this tool should be skipped in favor of `linkedin_account_stats` or `analytics_account`.

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