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The Profound Agency

by io.github.Jfromtheroc
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Quick AI visibility check

quick_visibility_check
Read-only

Five basics of whether AI systems can read a website, checked instantly from its public pages: AI crawlers allowed in robots.txt, an llms.txt, Organization and FAQ structured data, and a title and description. Free, no score, nothing stored. For the full audit — scored out of 100 and reviewed by a person — use request_audit.

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": {
      "website": "<website>"
    },
    "name": "quick_visibility_check"
  }
}

Input Schema

NameRequiredDescriptionDefault
websiteYesThe site to check. A domain is enough, e.g. "example.com".

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already establish readOnly/openWorld/non-destructive, and the description adds genuinely useful non-annotation context: instant execution, free of charge, no scoring, nothing stored, and that it works only from public pages. It stops short of describing failure modes or rate limits, so not quite a 5.

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?

Two sentences, zero filler, and the highest-value information (what is checked, plus the free/instant constraints) is front-loaded before the sibling routing pointer.

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 pre-empts the return value by listing the five checks, and it covers cost and storage semantics. It could say more about how results are presented, but for a one-param read-only probe it is close to complete.

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% and the single 'website' parameter is documented there with a format example ('example.com'), so the schema does the heavy lifting. The description adds no syntax or format detail beyond the schema – baseline 3.

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?

States a specific verb and resource ('whether AI systems can read a website') and enumerates the exact five checks performed (robots.txt crawler access, llms.txt, Organization/FAQ structured data, title/description). It explicitly distinguishes itself from the sibling request_audit, so an agent can route without opening either schema.

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?

Gives explicit when-to-use ('checked instantly from its public pages', 'free, no score') and names the alternative with its selecting condition ('For the full audit — scored out of 100 and reviewed by a person — use request_audit'). Nothing is left to inference.

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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