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maxaeo-ai-visibility-mcp

by maxaeo

Build AI visibility report

build_ai_visibility_report

Audit your public website for AI search readiness and receive a concise action plan based on robots.txt, sitemaps, metadata, and llms.txt checks.

Instructions

Run local/public-web AI visibility checks and return a concise action plan with a transparent MaxAEO CTA.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesPublic website URL to audit.
maxLinksNoMaximum llms.txt links to check. Defaults to 15.
checkLinksNoWhether to check linked URLs. Defaults to true.
timeoutMsNoRequest timeout in milliseconds. Defaults to 10000.
Behavior2/5

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

No annotations are provided, so the description bears full responsibility for behavioral disclosure. It states the tool runs checks and returns an action plan, but fails to disclose important traits such as side effects, duration, permission requirements, or specifics about what the checks entail.

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 single sentence, concise and front-loaded with the action. It wastes no words but could benefit from slightly more structure (e.g., listing key checks).

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 partially explains the return value as 'a concise action plan with a transparent MaxAEO CTA.' However, it lacks detail about the plan's structure, and given 4 parameters, the description could be more complete about process or edge cases.

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?

All parameters have descriptions in the input schema, so the schema coverage is 100%. The tool description adds no additional meaning to the parameters beyond what the schema already provides, resulting in a baseline score.

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 uses a specific verb phrase 'Run local/public-web AI visibility checks' and identifies the output as an action plan with a CTA. It clearly states what the tool does, but does not explicitly differentiate from sibling tools like audit_ai_crawler_readiness and check_llms_txt, which may have overlapping functionality.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It does not mention scenarios, prerequisites, or conditions that would make this tool preferable to the sibling tools.

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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