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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.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "projectId": "<projectId>",
      "siteId": "<siteId>"
    },
    "name": "list_ai_visibility_prompts"
  }
}

Input 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, destructiveHint=false, and openWorldHint=false, so safety is covered. The description adds what each row contains (visibility, position, named brands), which is useful, but says nothing about default time windows, pagination, or how the engine/date filters change results.

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?

A single front-loaded sentence with zero filler, and the return fields are listed immediately after the verb. Its brevity is close to the right size, though it spends its only clause on outputs rather than on the parameters the schema leaves undocumented.

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?

With six undocumented parameters, no output schema, and no annotation detail beyond read-only, the definition is too thin: required scoping, date semantics, engine filtering, and result shape/paging are all unaddressed. What is present is accurate but far from sufficient for correct invocation.

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

Parameters2/5

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

Schema description coverage is 0% across six parameters, so the description carries the full burden — yet it says nothing about the required projectId/siteId scope, the from/to date-time bounds, or the single 'engine' vs plural 'engines' filters. An agent cannot tell from the text whether omitting dates means 'all time' or a default window.

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?

Names a specific verb ('List') and a specific resource ('tracked prompts'), and even enumerates what comes back (visibility, position, brands named in each answer). It implicitly separates itself from the 'prompt_runs' sibling by describing prompts rather than runs, but never states that distinction explicitly.

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 when-to-use guidance, no mention of when to prefer 'list_ai_visibility_prompt_runs' or 'get_ai_visibility_overview', and no stated prerequisites such as needing a project and site scope. The agent must infer the tool's role 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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