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ai_visibility_audit

Check a URL origin's robots.txt and llms.txt to determine AI crawler access and discoverability.

Instructions

Check robots.txt AI crawler access and llms.txt presence for a URL's origin.

Fetches {origin}/robots.txt and checks each known AI crawler agent. Also checks for {origin}/llms.txt (Model Context Protocol discoverability file). No authentication required.

Verdicts: open (all AI crawlers allowed) | partial (some blocked) | closed (all blocked or disallow all) | fetch_error.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.2.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden and usefully states 'No authentication required', describes fetching robots.txt and checking each known AI crawler agent, and lists verdicts including fetch_error. It does not disclose rate limits, caching, or redirect behavior, but the core behavioral profile is well communicated.

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 front-loaded with the core action, then supplies necessary execution details and a compact verdict legend. Every sentence earns its place with no redundant or vague language.

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?

An output schema exists, so return values need not be explained, and the description covers what is fetched, authentication requirements, and verdict meanings. It is nearly complete, though explicit usage guidance relative to sibling tools would improve it further.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It clarifies that the url parameter is used to derive an origin by specifying 'for a URL's origin' and showing that only {origin}/robots.txt and {origin}/llms.txt are fetched, which is the key semantic distinction for this single required 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?

States a specific verb and resource: checks robots.txt AI crawler access and llms.txt presence for a URL's origin. It clearly distinguishes itself from siblings like ai_overviews_impact by focusing on crawler access files rather than AI Overview performance.

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 implies usage by stating the exact audit it performs, but it does not name alternative tools, when to prefer them, or when not to use this tool. Context is clear enough for a specialized audit, yet explicit routing guidance is absent.

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