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audit_site

Runs a comprehensive AI visibility audit across 58+ checks in 12 categories, covering AEO, GEO, and agent readiness. Generates an AI Identity Card with mention readiness and detected competitors to reveal optimization gaps.

Instructions

Full AI visibility audit across 58+ checks in 12 categories: AEO (structured data, meta & technical, AI accessibility, content quality), GEO (brand narrative, citation readiness with 3 research-backed checks, authority signals, entity definition), and Agent Readiness (machine identity, API discoverability, structured actions, programmatic access). Returns AI Identity Card with mention readiness and detected competitors. Requires API key (set AEO_API_KEY env var). $1.00 per call.

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": {
      "url": "<url>"
    },
    "name": "audit_site"
  }
}

Input Schema

Name	Required	Description	Default
`url`	Yes
`pages`	No
`categories`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.2.1Aug 23, 2026

TDQS

A3.7/5.0

Behavior4/5

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

No annotations are present, so the description carries the behavioral disclosure burden. It does well by revealing the API key requirement, the cost per call, the returned AI Intelligence Card, and detected competitors. It does not explicitly say the operation is read-only, but 'audit' strongly implies no destructive side effects.

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?

The description is a compact, information-dense paragraph with no filler. The main purpose is front-loaded, and the category breakdown is structured readably. It is lengthy but each clause adds useful information, though the inline list makes the sentence heavier than necessary.

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

Completeness3/5

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

The description covers the tool's purpose, authentication, cost, output, and high-level scope. However, it leaves parameter semantics unexplained, particularly pages and categories, which are central to configuring the audit. The existence of an output schema mitigates return-value uncertainty, but the request-level gaps remain.

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%, and the description does not explain the parameters. The url parameter is obvious, but pages and categories are undocumented beyond names/defaults, leaving an agent uncertain about allowed values and semantics. The category list inside the description gives some context, but not enough to correctly set categories.

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?

The description names a specific verb and resource: 'Full AI visibility audit' and explains the scope across 58+ checks in 12 categories. It further enumerates the categories and returns, making the purpose concrete and distinguishing it from scanning, comparing, or fixing.

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?

The description clearly implies this is the tool for a comprehensive AI visibility audit, but it never explicitly states when to use it instead of the sibling scan_site, compare_sites, or fix_site. There is no exclusions or alternative-routing guidance, so the intended usage is only inferred.

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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