Seonix

AI visibility

get_ai_visibility

Read-onlyIdempotent

AI Visibility: how often the brand appears in the answers of AI assistants (ChatGPT, Gemini, Claude, Google AI) for the project's tracked questions. Returns the overall score with its sample size, the per-engine breakdown, the weekly history, the competitors named, the top cited sources and the questions where the brand is absent. Checks run automatically once a week for projects on a paid plan; this tool only reads.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_ai_visibility"
  }
}

Input Schema

Name	Required	Description	Default
`project_id`	No	Project id or slug.
`include_answers`	No	Include the answer excerpt and cited sources per question, and the full list of questions where the brand is absent (default false).

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedNov 10, 2026

changedInput schema / properties / include_answers / description

Previous value: -"Include the answer excerpt and cited sources per prompt (default false)."New value: +"Include the answer excerpt and cited sources per question, and the full list of questions where the brand is absent (default false)."

First observedOct 25, 2026

TDQS

A3.9/5.0

Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, and the description adds real context beyond them: weekly automated refresh cadence, paid-plan gating, and a full enumeration of what the read returns (score with sample size, per-engine breakdown, weekly history, competitors, cited sources, absent questions). It stops short of saying what happens on an unpaid plan or whether stale/empty results are possible.

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?

Front-loaded with the definition, then the return payload, then the operational caveat. The payload enumeration is dense but justified because there is no output schema; the only mild inefficiency is the list-like mid-sentence run-on.

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 correctly compensates by naming the returned fields, and it covers cadence and plan gating for a read-only tool. Remaining gaps are minor: behavior on non-paid plans and whether the question lists are paginated or bounded.

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% and both parameters are fully documented in the schema, including the include_answers default and its effect. The description adds no parameter-level meaning beyond that, so the baseline 3 applies.

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?

Names a specific resource and metric: brand appearance frequency in AI assistant answers (ChatGPT, Gemini, Claude, Google AI) across the project's tracked questions. That domain is distinct enough from the traffic-oriented sibling ga4_ai_traffic that an agent can pick this tool on the description alone.

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?

Provides a precondition ('Checks run automatically once a week for projects on a paid plan') that tells the agent when data exists, but never says when to prefer this over ga4_ai_traffic or other AI/traffic tools, and gives no exclusions or failure-mode guidance for free-plan projects.

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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