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Fourward AI visibility tools

AI crawler checker

check_ai_crawlers
Read-onlyIdempotent

Shows which of 20 AI crawlers can read a website's homepage: AI search and answer bots (OAI-SearchBot, ChatGPT-User, Claude-SearchBot, PerplexityBot, Googlebot, Bingbot and more) and AI training bots (GPTBot, ClaudeBot, Google-Extended, CCBot and more). Applies the site's robots.txt rules per bot the way RFC 9309 and Google do, tests the firewall by fetching the homepage as a browser and as four AI bots, and reports llms.txt and sitemap lines. Takes about 10 seconds.

Input Schema

NameRequiredDescriptionDefault
domainYesThe website to check, as a domain such as example.com. A full URL also works; only the hostname is used.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior5/5

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

Annotations already cover read-only, idempotent, non-destructive and open-world behavior, and the description still adds substantial context: it applies robots.txt rules per RFC 9309 and Google's interpretation, fetches the homepage as a browser and four AI bots to test firewalls, reports llms.txt and sitemap lines, and discloses a ~10 second runtime. This is exactly the kind of method-and-cost disclosure that helps an agent plan the call.

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 core purpose is front-loaded in the first clause, with the bot enumeration parenthetically contained. The second sentence carries method, output, and timing without filler. The long first sentence is dense but every clause earns its place.

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?

For a single-parameter, non-destructive read tool with no output schema, the description supplies everything needed: scope (homepage), method (robots.txt semantics, dual fetching), outputs (crawler readability, firewall behavior, llms.txt, sitemap), and runtime. Nothing an agent needs in order to call it or interpret the result is missing.

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%: the single `domain` parameter is fully documented in the schema, including that a full URL works and only the hostname is used. The description adds only the framing that the homepage is what gets checked, so it neither needs to nor does add parameter-level detail beyond the schema. Baseline 3 is appropriate.

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 opens with a specific verb and resource ('Shows which of 20 AI crawlers can read a website's homepage') and even enumerates the bot categories covered. It is unambiguous about what the tool does, but it never mentions the sibling check_ai_visibility or explains how the two differ, which keeps it from a 5.

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?

Usage is only implied: an agent can infer this is the tool for checking crawler access to a site. There is no explicit guidance on when to choose this over check_ai_visibility, no prerequisites, and no exclusion conditions.

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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