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sparrow84001

SEO, AEO, GEO & Digital Marketing Audit + Safe Fix MCP Server

by sparrow84001
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seo_audit_aeo

Audit a live URL or local file for Answer Engine Optimization readiness: assess concise answer blocks, question-based subheadings, FAQ schema alignment, and citation potential for AI Overviews and Perplexity.

Instructions

Audits content for Answer Engine Optimization (AEO): Evaluates concise 40-60 word direct answer definition blocks, question-based H2/H3 subheadings (What/How/Why), FAQ schema alignment, and citation readiness for Google AI Overviews and Perplexity.

USAGE GUIDELINES:

  • Use when optimizing content to win conversational AI search citations, direct answers, and Perplexity summaries.

  • Do NOT use for brand knowledge-graph entity reconciliation; use 'seo_audit_geo' instead.

  • Do NOT use for standard on-page metadata; use 'seo_audit_onpage' instead.

BEHAVIORAL TRANSPARENCY:

  • Safe, read-only diagnostic evaluation. No file modifications.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
targetYesTarget live URL (e.g. "https://example.com/topic") or local file path to audit.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.1.1
    • changedInput schema / properties / target / description
      Previous value: -"Target file path or live URL."New value: +"Target live URL (e.g. \"https://example.com/topic\") or local file path to audit."
  2. First observedv0.1.0

TDQS

A4.7/5.0
Behavior5/5

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

No annotations are provided, so the description carries full burden. It explicitly discloses 'Safe, read-only diagnostic evaluation. No file modifications,' which is a clear behavioral statement beyond the tool name and schema.

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 well-structured with purpose, usage guidelines, and behavioral transparency sections. Each sentence provides useful context without fluff or redundancy.

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 the simple single-parameter input and no output schema, the description sufficiently explains what the tool evaluates and when to use it. It provides enough context for an agent to correctly select and invoke the tool.

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%, so baseline is 3. The description does not add further parameter semantics beyond the schema, but none are needed given the single simple 'target' parameter.

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 clearly states the tool audits content for Answer Engine Optimization, with specific evaluation criteria. It distinguishes itself from sibling tools by naming seo_audit_geo and seo_audit_onpage as alternatives for different use cases.

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

Usage Guidelines5/5

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

Explicitly states when to use ('when optimizing content to win conversational AI search citations...') and when not to use, with concrete alternative tool names for excluded scenarios.

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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