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Run an AI visibility check

visibility_check

Ask every tracked buyer question on each chosen assistant, with web search on, and measure how often the business is named, where, how favourably, against which competitors, and which sites the assistants cite. Takes a few minutes. When it finishes, the result is the same report as visibility_report. Costs $0.04 per answer (one question on one assistant); nothing if none are found. Runs in the background: the reply has a call_id; poll it with the account_get_call tool or GET /v1/calls/.

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": {
      "website": "<website>"
    },
    "name": "visibility_check"
  }
}

Input Schema

NameRequiredDescriptionDefault
websiteYesThe business website, e.g. https://acme.com

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Adds substantial behavior beyond annotations: it takes minutes, runs in the background, returns a call_id for polling via account_get_call or the REST endpoint, and charges $0.04 per answer with no charge if nothing is found. Annotations already cover open-world/non-idempotent/non-destructive semantics, and the description adds the operational context an agent needs.

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?

Front-loads what the check does, then covers duration, output equivalence, cost, and background polling in compact sentences. Every sentence carries operational value for an agent.

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

Completeness5/5

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

Given no output schema, the description explains the output equivalence to visibility_report and the asynchronous result retrieval path. It also covers cost, duration, and billing edge cases, leaving little an agent needs for correct invocation.

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 description coverage is 100% for the single website parameter, so the schema already documents it fully. The description adds useful context about tracked questions and assistants, but does not add meaning to the website parameter itself; baseline 3 is appropriate.

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

Purpose5/5

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

States a specific action: asking tracked buyer questions on chosen assistants and measuring naming frequency, placement, sentiment, competitors, and citations. It distinguishes itself from visibility_report by explaining that it produces the same report, and it names the background call flow with account_get_call.

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

Usage Guidelines4/5

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

Clearly signals when to use it: to run a fresh visibility check, with cost and duration called out, and it points to visibility_report as the equivalent output format. It does not explicitly state when not to use it versus visibility_report or visibility_setup, so it stops short of full alternative routing.

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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