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Check AI crawler access

check_ai_crawlers
Read-onlyIdempotent

Reads a website's robots.txt and reports, for 11 AI crawlers (GPTBot, OAI-SearchBot, ChatGPT-User, ClaudeBot, Claude-SearchBot, PerplexityBot, Google-Extended, Applebot-Extended, Meta-ExternalAgent, CCBot, Bytespider), whether each may reach the given page. Separates AI search crawlers (decide if the site appears in ChatGPT, Claude and Perplexity answers) from training crawlers. Also reports llms.txt and declared sitemaps.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesWebsite or page address, e.g. example.com or https://example.com/pricing

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
agentsYes
llmsTxtNo
sitemapsNo
robotsTxtYes
httpStatusNo
contentSignalsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, covering the safety and idempotency profile. The description adds useful scoping context (reads robots.txt, reports 11 named crawlers, llms.txt and sitemaps) for an open-world network read, but doesn't mention rate limits, caching, redirects, or failure modes when robots.txt is missing. With annotations carrying the safety burden, a 3 is appropriate.

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?

Three dense sentences with zero filler, front-loaded on the core action and then the output taxonomy (search vs training crawlers, llms.txt, sitemaps). Every sentence earns its place and the crawler list is information the agent needs, not padding.

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 shape needn't be explained, and the description still previews the key result categories (per-crawler verdicts, search vs training split, llms.txt, sitemaps). It is complete enough to call correctly; missing only edge-case behavior (no robots.txt, timeouts) which is minor for a read-only checker.

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?

Single parameter with 100% schema coverage, so the schema already documents the url format with an example. The description adds the intent that the url points at a 'given page' whose reachability is being tested, which clarifies semantics slightly beyond the schema. Baseline for a well-covered single param, nudged up by that framing.

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 precise verb+resource: reads robots.txt and reports per-crawler access for a named page. It names the exact 11 crawlers and the llms.txt/sitemap outputs, so an agent knows exactly what comes back without opening the output schema. It is distinguishable from siblings like explain_ai_crawler and view_page_as_ai_crawler by being the raw robots.txt access check.

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 the use case (determining whether AI crawlers may reach a page) and even hints at the search-vs-training distinction, but it never explicitly says when to choose this tool over explain_ai_crawler or view_page_as_ai_crawler. The routing between these four siblings 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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