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

Annotations already declare readOnly=true, idempotent=true, and non-destructive, so safety is covered; the description adds operationally important context beyond that: a paid plan requirement (Lite or Pro), a Bearer dashboard token for auth, and the fact that results are scoped to the domain on the subscription. It says nothing about refresh cadence or what an empty/insufficient-data day looks like, keeping it short of a 5.

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 tight sentences that lead with the returned data shape, then the purpose, then the access requirements. Nothing is wasted, though the final sentence ('Covers the domain on your subscription') is slightly terse and its connection to the auth sentence could be tighter.

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 parameters and no output schema, the description carries the burden of explaining return shape and access requirements, and it does both: daily granularity, two metrics, plan tier, and token auth. Only minor gaps remain, such as data freshness and behavior when a domain lacks 30 days of history.

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 tool takes zero parameters, so there is no per-parameter semantics to explain and the baseline is 4. The description usefully notes the implicit scope (the subscription's domain) and the fixed 30-day window, which is the closest analogue to parameter meaning here.

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 exactly what the tool returns: one point per day for the last 30 days, containing a visibility score and a count of answers recommending your product. This is concrete and distinguishable from the sibling get_visibility (a point-in-time read) by its explicit 30-day daily series, though it never names that sibling to make the contrast explicit.

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?

It gives clear usage context: 'Use it to see whether your changes moved AI search engines,' which tells the agent this is a trend/measurement tool rather than a snapshot lookup. It stops short of naming alternatives such as get_visibility or stating when not to use it, so the agent must infer the snapshot-vs-trend split.

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