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AIEthos-ai

mcp-ethostron-live

Official

aiethos_geo_quickscan

Run a quick GEO audit on any URL to check AI bot crawlability, Schema.org health, and direct-answer readability, then identify citation gaps for ChatGPT, Perplexity, and Google AI Overviews.

Instructions

Performs a fast Generative Engine Optimization (GEO) audit on a domain or URL. Analyzes AI bot crawlability, Schema.org microdata health, direct-answer readability, and identifies top citation gaps for LLMs like Perplexity, ChatGPT, and Google AI Overviews.

Input Schema

NameRequiredDescriptionDefault
urlYesThe full target URL or root domain to audit (e.g., 'https://example.com' or 'example.com').
brand_nameNoOptional brand name to check entity citations for.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full disclosure burden. It implies a passive read-only audit and lists what gets analyzed, but says nothing about whether the scan fetches live pages, how long it takes, rate limits, or what the result contains — leaving the agent to guess at cost and 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?

Two front-loaded sentences with the action first and the analysis scope second; almost every clause carries information. The trailing "for LLMs like Perplexity, ChatGPT, and Google AI Overviews" is slightly padded but does convey the evaluation targets.

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?

With no output schema, the description should say roughly what an audit returns (scores, findings, gap list). It names the analysis dimensions but not the deliverable, so an agent knows what the tool inspects but not what it will get back.

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%, so both parameters are already fully documented in the schema, including accepted URL/domain formats and the optional brand_name. The description adds no parameter-level meaning beyond that, which is the expected baseline rather than a strength.

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?

The description gives a specific verb and resource ("Performs a fast GEO audit on a domain or URL") and enumerates the four analysis dimensions, so the purpose is unmistakable. It does not, however, distinguish itself from the sibling aiethos_check_llm_citations, even though "identifies top citation gaps" overlaps that tool's apparent domain.

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?

"Fast" implies a lightweight variant exists, but the description never states when to choose this over aiethos_check_llm_citations or aiethos_preview_ethostron_fix, and gives no prerequisites or exclusions. Usage must be inferred from the tool name and the word "quickscan."

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.