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Get my ai visibility coverage

get_my_ai_visibility_coverage
Read-onlyIdempotent

Which domains a customer's AI Visibility plan watches: the plan's own site plus the extra domains they have added, each with how it was verified and its latest grade (null grade = not scanned yet, say "pending", never "passing"). Also how many of the slots are used. Refused when AI Visibility is not on the plan. Read-only.

Input Schema

NameRequiredDescriptionDefault
domainYesThe hosting plan's domain.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior5/5

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

Annotations declare read-only/idempotent, and the description adds genuinely new behavior: the call is refused when AI Visibility is absent from the plan, and a null grade means unscanned, which must be reported as "pending", never "passing". That last instruction actively prevents a plausible hallucination, which is high-value disclosure beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Dense and front-loaded: the resource is stated first, then the contents, then the refusal rule. It is a single long sentence with parenthetical asides, but nearly every clause carries operational meaning; only "Read-only" is redundant with the annotations.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description does the necessary work of describing the returned fields (domains, verification, grade, slot counts) and the refusal case. It stops short of explaining how slot usage is represented or what verification values look like, which leaves a small gap for a tool whose return shape is undocumented elsewhere.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with a single documented parameter ("The hosting plan's domain"). The description only obliquely reinforces this via "the plan's own site", adding no format, validation, or matching detail beyond the schema, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Opening clause names the specific resource: the domains an AI Visibility plan watches, plus their verification method, latest grade, and slot usage. It is clearly a read of plan coverage rather than a scan, but it never names the sibling check_ai_visibility that an agent might confuse it with.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

'Refused when AI Visibility is not on the plan' gives the agent one useful precondition for calling it. However, there is no statement of when to prefer this over check_ai_visibility or plan_ai_visibility_fixes, so the agent must infer the distinction from the name alone.

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

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