Benchmark vs industry/geo

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

Annotations already declare readOnlyHint and destructiveHint, so the safety profile is covered. The description goes further by disclosing the subscription requirement, the trial terms, and the aggregated-data basis, which are behavioral traits not present in annotations. It also clarifies the fallback path, adding real value beyond structured metadata.

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?

The description is two sentences, front-loaded with purpose and usage, then the subscription detail is appended. It's somewhat long but each part earns its place, explaining prerequisites and a routing action. Slight verbosity in the trial terms but acceptable.

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?

Given the low complexity (3 params, no output schema), the description covers purpose, usage, prerequisite, and alternatives. It does not detail the output format, but it points to get_sample_audit for exactly that, and the annotations carry the safety context. Minor gap: it doesn't clarify default behavior when geo/industry are omitted, but the schema implies they are optional overrides.

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 baseline is 3. The description does not add extra meaning to parameters beyond the schema, though it mentions industry and location in the purpose. No significant gap, but no added value either.

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 a clear verb and resource: 'Benchmark a website's AI visibility against its industry and location.' It differentiates from siblings by explicitly contrasting with absolute numbers and mentioning the use case for percentile/peer context, and it names get_sample_audit as an alternative for non-subscribers.

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?

The description gives explicit triggers ('how do I compare to others in my space,' 'is this a good score for my industry') and a clear when-not case ('rather than an absolute number'). It also prescribes a fallback action (call get_sample_audit) when the user lacks a subscription, providing unambiguous routing among siblings.

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