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List AI visibility prompts

list_ai_visibility_prompts
Read-only

List the tracked prompts with visibility, position, and the brands each answer names.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNo
fromNo
engineNo
siteIdYes
enginesNo
projectIdYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, openWorldHint=false, and destructiveHint=false, so the safety profile is covered. The description adds some useful context by naming what the returned records include (visibility, position, brands each answer names), but it does not disclose pagination, filtering behavior, rate limits, or authorization requirements beyond what annotations provide.

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

Conciseness5/5

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

The description is a single efficient sentence with the action front-loaded and no wasted words. It is appropriately sized for the amount of information it attempts to convey.

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

Completeness2/5

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

For a list tool with two required IDs, four optional filters (date range and engine filters), no output schema, and 0% schema description coverage, the description is materially incomplete. It omits required parameters, filter semantics, pagination, and a clear definition of 'visibility' or 'position', so an agent lacks enough context to invoke it correctly without inspecting the schema.

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

Parameters1/5

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

Schema description coverage is 0% across six parameters, and the description supplies no parameter information at all. It does not mention the required projectId/siteId, the optional from/to date range, or the engine/engines filters, leaving all parameter semantics undocumented.

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?

The description states a specific verb ('List') and resource ('tracked prompts') and outlines returned fields (visibility, position, brands each answer names). It is clear what the tool does, but it does not explicitly distinguish itself from siblings like list_ai_visibility_prompt_runs or get_ai_visibility_overview.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus alternatives, no mention of prerequisites, and no exclusions. The implied use is simply to list prompts, but the description provides no routing information for the many related AI-visibility tools.

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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