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

Annotations already declare readOnlyHint and openWorldHint, so safety is covered. The description adds genuinely new behavioral facts: the 90-data-point cap and that the call is free, plus the dependency on a prior audit. It does not explain ordering, gaps, or granularity of the trend points.

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 with zero filler; the resource and data cap are front-loaded, the cost note and usage cue follow. Every sentence carries distinct information.

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 adequately signals the return shape (a historical trend series, capped at 90 points) and the precondition for calling it. Missing only minor detail such as cadence or ordering of the data points.

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 coverage is 100% and both parameters are documented in the schema. The description reinforces that brand/domain must match past audits, but adds no syntax or format detail beyond the schema. Baseline 3 applies when the schema does the heavy lifting.

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+resource ('Get the historical AI-visibility score trend') with scope ('up to 90 data points') and a clear precondition ('brand + domain that has been audited before'). It implicitly separates itself from the audit siblings but never names get_brand_audit or list_brand_audits explicitly.

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?

'Use to show visibility change over time' gives clear when-to-use context, and the 'has been audited before' clause states a prerequisite. It stops short of naming alternatives (e.g., a single-snapshot audit) or stating when not to use it.

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