AI access report

slate.com

Open to answer engines, blocks 17 training crawlers, refuses AI user agents at the edge.

4 failing 6 partial 17 passing Scanned 1 hour ago · 2 scans on record trend

Reach

27.1 / 40

Whether AI crawlers and answer-engine fetchers are permitted to request the page at all, in robots.txt, in robots directives, and at the edge.

Readability

20.6 / 25

Whether a fetcher that does not execute JavaScript receives the actual content, in markup an extractor can segment.

Structure

20 / 20

Machine-readable markup that states the page's type, entities, canonical URL, and discrete facts instead of leaving them to be inferred.

Attribution

4 / 15

Signals that let an answer engine name the author, date the content, resolve the publisher, and cite it under known terms.

Who is allowed to read this site 0 of 24 answer engines blocked

Crawler	Operator	Uses content for	robots.txt	Live request
GPTBot Crawls content that may be used to train OpenAI's generative AI foundation models.	OpenAI	Model training	blocked Disallow: /	refused 402
OAI-SearchBot Indexes pages so they can be surfaced and cited in ChatGPT search results, not for training.	OpenAI	Answer index	allowed	refused 402
ChatGPT-User Fetches a page when a ChatGPT user or GPT Action asks for it; user-initiated, so robots rules may not apply.	OpenAI	Live retrieval	allowed	not probed
OAI-AdsBot Visits pages submitted as ChatGPT ads to check policy compliance and ad relevance; not used for model training.	OpenAI	Live retrieval	allowed	not probed
ClaudeBot Collects web content that may contribute to training Anthropic's models; honors Crawl-delay.	Anthropic	Model training	blocked Disallow: /	refused 402
Claude-User Retrieves pages on demand when a Claude user's question needs live web content.	Anthropic	Live retrieval	allowed	not probed
Claude-SearchBot Indexes content to improve the relevance and accuracy of Claude's search results.	Anthropic	Answer index	allowed	not probed
anthropic-ai Legacy token widely blocked for Anthropic training; Anthropic now documents ClaudeBot, Claude-User and Claude-SearchBot.	Anthropic	Model training	allowed	not probed
Google-Extended Control token with no user agent of its own; governs Gemini training and grounding use of Googlebot data.	Google	Model training	blocked Disallow: /	not probed
Googlebot Crawls and renders pages for Google Search, Images, Video, News and Discover.	Google	Answer index	allowed	not probed
Googlebot-News Robots token controlling Google News inclusion; crawling itself uses the Googlebot user agents.	Google	Answer index	allowed	not probed
Google-CloudVertexBot Crawls sites at a site owner's request to build Vertex AI agents; no effect on Google Search.	Google	Live retrieval	allowed	not probed
GoogleOther Generic Google crawler used by product teams for one-off fetches such as internal research and development.	Google	Model training	blocked Disallow: /	not probed
Applebot Crawls for Siri, Spotlight and Safari search; falls back to Googlebot rules and ignores Crawl-delay.	Apple	Answer index	allowed	not probed
Applebot-Extended Control token with no user agent; disallowing it excludes crawled content from Apple foundation model training.	Apple	Model training	blocked Disallow: /	not probed
Bingbot Indexes pages for Bing search and the Copilot answers that are grounded in the Bing index.	Microsoft	Answer index	allowed	not probed
msnbot Legacy Microsoft search crawler token still honored alongside bingbot.	Microsoft	Answer index	allowed	not probed
PerplexityBot Indexes and links pages in Perplexity search results; not used to collect foundation model training data.	Perplexity	Answer index	allowed	refused 402
Perplexity-User ignores robots Fetches a page for a specific user question; Perplexity documents that it generally ignores robots.txt.	Perplexity	Live retrieval	allowed	not probed
Meta-ExternalAgent Crawls the web to train Meta's foundation AI models and to index content directly into products.	Meta	Model training	blocked Disallow: /	not probed
Meta-ExternalFetcher ignores robots Fetches individual links for agentic AI tasks; Meta documents that it may bypass robots.txt.	Meta	Live retrieval	allowed	not probed
FacebookBot Crawls public pages to improve language models behind Meta's speech recognition technology.	Meta	Model training	blocked Disallow: /	not probed
Meta-WebIndexer Indexes pages so Meta AI can cite and link them in its search answers.	Meta	Answer index	allowed	not probed
Meta-ExternalAds Crawls the web to improve Meta's advertising and other business products and services.	Meta	Model training	allowed	not probed
facebookexternalhit ignores robots Fetches shared links for Facebook, Instagram and Messenger previews; may bypass robots.txt for integrity checks.	Meta	Live retrieval	allowed	not probed
Bytespider ignores robots Downloads content to train ByteDance LLMs and is widely reported to ignore robots.txt directives.	ByteDance	Model training	blocked Disallow: /	not probed
TikTokSpider ignores robots Fetches shared URLs for TikTok link previews and feeds; not expected to follow robots.txt.	ByteDance	Live retrieval	allowed	not probed
Amazonbot Crawls for Amazon product and Alexa answers and may use the content to train Amazon AI models.	Amazon	Model training	blocked Disallow: /	not probed
Amzn-SearchBot Indexes content for Amazon search experiences such as Alexa; does not crawl for generative AI training.	Amazon	Answer index	allowed	not probed
Amzn-User ignores robots Fetches live pages to answer a user's Alexa question; Amazon documents it may not follow all robots.txt rules.	Amazon	Live retrieval	allowed	not probed
CCBot Builds the open Common Crawl web archive, a common source of LLM pretraining corpora.	Common Crawl Foundation	Archive	blocked Disallow: /	not probed
Diffbot Extracts structured page data for Diffbot's knowledge graph, which is licensed to AI customers.	Diffbot	Model training	allowed	not probed
omgili Collects forum, news and blog content that Webz.io sells as web data feeds, including for AI training.	Webz.io	Model training	blocked Disallow: /	not probed
omgilibot Legacy Omgili search crawler token still blocked alongside the current omgili agent.	Webz.io	Model training	blocked Disallow: /	not probed
AI2Bot Collects web text for Ai2's open datasets used to train open language models such as OLMo.	Allen Institute for AI	Model training	blocked Disallow: /	not probed
cohere-ai Retrieves pages to answer user-initiated prompts in Cohere's enterprise AI products.	Cohere	Live retrieval	allowed	not probed
cohere-training-data-crawler Downloads training data for the large language models behind Cohere's enterprise AI products.	Cohere	Model training	blocked Disallow: /	not probed
MistralAI-User Fetches pages on demand so Mistral's Vibe assistant can answer a question with live, cited web content.	Mistral AI	Live retrieval	allowed	not probed
MistralAI-Index Indexes content for Mistral search behind Vibe answers; not used for generative AI training.	Mistral AI	Answer index	allowed	not probed
MistralAI-Training Crawls web content to build datasets for training Mistral's generative AI models.	Mistral AI	Model training	allowed	not probed
DuckAssistBot Crawls pages in real time for DuckDuckGo's cited AI-assisted answers; not used for model training.	DuckDuckGo	Live retrieval	allowed	not probed
YouBot Indexes pages for You.com search results and the AI answers built on that index.	You.com	Answer index	allowed	not probed
PanguBot Collects web content used to train Huawei's PanGu family of large models.	Huawei	Model training	blocked Disallow: /	not probed
Timpibot Crawls pages for Timpi's decentralized index, which is also used as LLM training data.	Timpi	Model training	blocked Disallow: /	not probed
ImagesiftBot Downloads public images plus surrounding text to build ImageSift's searchable image index.	ImageSift (Hive)	Model training	allowed	not probed
Kangaroo Bot Scrapes site content into datasets used to train the Kangaroo LLM.	Kangaroo LLM	Model training	blocked Disallow: /	not probed
SemrushBot-OCOB Crawls pages to feed Semrush's ContentShake AI writing tool.	Semrush	Model training	allowed	not probed
Scrapy Generic scraping framework often used to build AI training datasets; obeys robots.txt only when ROBOTSTXT_OBEY is on.	Zyte (open-source framework)	Model training	blocked Disallow: /	not probed

Two of these columns matter differently. robots.txt is what the site declares. Live request is what actually happened when we sent a real request using that crawler's user agent from a datacentre IP, which is how edge blocking, rate limits and challenge pages show up even when robots.txt looks permissive.

Reach 27.1 / 40

✗

Edge returns 403, 429, or a challenge to AI user agents

Requests identifying as gptbot, oai-searchbot, perplexitybot, claudebot were refused at the edge (HTTP 402 for bot UA only; HTTP 402 for bot UA only; HTTP 402 for bot UA only; HTTP 402 for bot UA only).

Why it matters. A permissive robots.txt is irrelevant if the edge answers an AI user agent with 403, 429, or a JavaScript challenge. Retrieval fetchers do not solve interstitials, so the assistant records a fetch failure and answers from another source.
Fix. Fetch the page with each AI user agent string and compare the status and byte count against a browser request. On Cloudflare, check whether the "Block AI bots" toggle in AI Crawl Control, a Bot Fight Mode rule, or a WAF custom rule on `cf.verified_bot_category` is catching the request, then narrow it: block the training category and add a skip rule for the retrieval agents you want citing you. Verified bots must not be handed Managed Challenge, since a challenge is a hard failure for a non-browser client. Re-test after every WAF or bot-management change, because these toggles are applied zone-wide.

for ua in "OAI-SearchBot/1.0" "ChatGPT-User/1.0" "Claude-User/1.0" \
          "Claude-SearchBot/1.0" "PerplexityBot/1.0" "Mozilla/5.0"; do
  code=$(curl -s -o /dev/null -w '%{http_code}' -A "$ua" https://example.com/)
  printf '%s\t%s\n' "$code" "$ua"
done

Reference

6 pt

Training crawlers are disallowed for this path

Blocked by robots.txt: GPTBot, ClaudeBot, Google-Extended, GoogleOther, Applebot-Extended, Meta-ExternalAgent, FacebookBot, Bytespider, Amazonbot, omgili, omgilibot, AI2Bot, cohere-training-data-crawler, PanguBot, Timpibot, Kangaroo Bot, Scrapy.

Why it matters. GPTBot, ClaudeBot, and CCBot collect pages into pretraining corpora, and Google-Extended and Applebot-Extended are opt-out tokens that govern whether already-crawled pages may be used for Gemini and Apple Intelligence. Disallowing them removes your text from the corpora models generalise from, which is a policy choice, not a bug.
Fix. Decide this deliberately rather than by inheriting a template. If you want your content in model weights, remove the `Disallow: /` groups for `GPTBot`, `ClaudeBot`, `CCBot`, `Google-Extended`, and `Applebot-Extended`. If you do not, keep those groups but scope them to the paths that matter and leave retrieval fetchers untouched, because `Google-Extended` and `Applebot-Extended` only control training use and never affect search or answer citation. Record the decision somewhere durable so the next robots.txt edit does not silently reverse it.

# Opt out of model training only.
User-agent: GPTBot
User-agent: ClaudeBot
User-agent: CCBot
User-agent: Google-Extended
User-agent: Applebot-Extended
Disallow: /

Reference

8 pt

robots.txt sets Crawl-delay, which most fetchers ignore

Crawl-delay of 10s is declared. Large crawlers may fetch only a few pages per hour, or ignore the directive entirely.

Why it matters. `Crawl-delay` is not in RFC 9309. Googlebot and OpenAI's fetchers ignore it, while some retrieval agents that do honour it will space requests seconds apart, which can exceed an answer engine's fetch timeout and leave the page uncited.
Fix. Remove `Crawl-delay` and handle load at the edge instead, with caching and rate limiting keyed on the client. If crawl volume is the real problem, cache HTML at your CDN so repeat fetches never reach the origin. Keep the file to standard directives (`User-agent`, `Allow`, `Disallow`, `Sitemap`) so parser behaviour is predictable.

# Remove non-standard throttling directives:
# Crawl-delay: 10

User-agent: *
Allow: /

Reference

2 pt

✓

Answer-engine fetchers are allowed to retrieve and cite this page

All 24 answer-engine fetchers are allowed to retrieve pages for citation.

12 pt

✓

No blanket disallow applies to this path

The wildcard group does not disallow the entire site.

5 pt

✓

robots.txt served as plain text with a 200 response

robots.txt served, 8922 bytes, 4 group(s).

3 pt

✓

Page is indexable, with no noindex directive

No noindex directive on the homepage.

2 pt

✓

Full-length snippet extraction is permitted

Snippets are not restricted by meta tags.

1 pt

✓

X-Robots-Tag header is absent or permissive

No restrictive X-Robots-Tag header.

1 pt

Readability 20.6 / 25

✗

Visible text is a small fraction of the HTML payload

Text is 2.2% of the 470 KB document; 216 KB is inline script.

Why it matters. Extractors strip scripts, styles, and wrapper markup before passing text to a model, and a page where content is a small fraction of the payload loses more of it to boilerplate removal. Inline JSON state blobs and deeply nested wrappers also push real text past the truncation limit of a retrieval context.
Fix. Move inline hydration state and large inline scripts out of the document, or fetch them after load instead of embedding them. Flatten wrapper `div` trees and let semantic elements carry the content, and keep utility-class soup out of the article body. Serve the same text without the boilerplate at a stable URL if you need a clean extraction target.

4 pt

Heading levels are missing, duplicated, or skipped

4 H1 and 87 headings total, 9 phrased as questions.

Why it matters. Chunkers split long pages on heading boundaries and carry the nearest heading into each chunk's metadata. A page with no `h1`, several competing `h1`s, or levels that skip from `h2` to `h4` produces chunks whose topic labels do not match their text, so retrieval matches the wrong passage.
Fix. Give every page one `h1` that names its subject, then nest `h2` and `h3` without skipping levels. Make each heading describe the section beneath it in words a reader would search for, rather than a label like "Overview". Style with CSS instead of choosing heading levels for their font size, and never use a heading tag for a caption or a button.

<h1>Robots.txt rules for AI crawlers</h1>
<h2>Training crawlers</h2>
<h3>GPTBot</h3>
<h3>ClaudeBot</h3>
<h2>Retrieval and citation fetchers</h2>
<h3>OAI-SearchBot</h3>

Reference

3 pt

✓

Substantive text is present in the server-rendered HTML

1695 words of text are present in the raw HTML. Most AI fetchers do not run JavaScript.

9 pt

✓

Primary content is wrapped in a semantic landmark

A <main> landmark marks the primary content.

3 pt

✓

Title is unique and describes the page in specific terms

Title is 61 characters: "Slate Magazine - Politics, Business, Technology, and the Arts"

3 pt

✓

Meta description provides an author-written summary

Meta description is 147 characters.

2 pt

✓

Document language is declared on the html element

Declared language: en.

1 pt

Structure 20 / 20

✓

Page ships JSON-LD structured data

4 JSON-LD node(s): NewsArticle, Organization, ImageObject, WebPageElement.

7 pt

✓

Structured data uses a specific type that matches the page

Recognized types: newsarticle, organization.

4 pt

✓

JSON-LD parses cleanly with recognised schema.org terms

All JSON-LD blocks parse cleanly.

3 pt

✓

Page declares a self-referential canonical URL

Canonical: https://slate.com/

3 pt

✓

XML sitemap is declared in robots.txt and returns 200

Sitemap found at https://slate.com/sitemaps/sitemap-index.xml.

2 pt

✓

Key facts are available in lists or tables

0 tables, 11 lists, 0 code blocks, 9 question headings.

1 pt

Attribution 4 / 15

✗

No /llms.txt index of canonical pages

No /llms.txt.

Why it matters. `/llms.txt` is a markdown file that points an assistant at the canonical pages for a site, so retrieval does not depend on which page a search happened to return. Its format is fixed: one `#` title, a `>` blockquote summary, then `##` sections of markdown links with short notes.
Fix. Publish `/llms.txt` as `text/plain` markdown: an `#` H1 with the project name, a `>` blockquote summary, optional plain paragraphs of context, then `##` sections whose bullets are `[title](absolute-url): note`. Link the pages you want quoted, put lower-priority links under an `## Optional` section, and prefer URLs that also serve clean markdown. Keep it generated from the same source as your sitemap so it does not drift, and remember it is a hint for assistants, not an access control mechanism.

# Example

> Example publishes reference documentation for the Widget API and guides for
> configuring crawler access.

Prefer the pages below over search results; each URL is canonical.

## Docs

- [Widget API reference](https://example.com/docs/api): endpoints, auth, limits.
- [Quickstart](https://example.com/docs/quickstart): first request in five minutes.

## Policies

- [Crawler policy](https://example.com/legal/crawlers): which agents we allow.

## Optional

- [Changelog](https://example.com/changelog): dated release notes.

Reference

4 pt

✗

No machine-readable author is attached to the page

No author or Person entity, which weakens the authority signals answer engines use.

Why it matters. An `author` property in structured data is what lets an answer engine name a person or organisation as the source and link the byline to a stable profile. A byline that exists only as styled text is not reliably associated with the document during extraction.
Fix. Add an `author` property to the page's `Article`, `BlogPosting`, or `NewsArticle` node, typed as `Person` or `Organization`, with a `name` and a `url` pointing at a real profile page. Give each author a stable `@id` and reuse it across posts so the entity consolidates. Keep the visible byline identical to the structured value, and avoid generic names such as "Admin" or "Staff Writer" where a real author exists.

{
  "@context": "https://schema.org",
  "@type": "BlogPosting",
  "headline": "Allow AI answer engines in robots.txt",
  "author": {
    "@type": "Person",
    "@id": "https://example.com/authors/dana-reyes#person",
    "name": "Dana Reyes",
    "url": "https://example.com/authors/dana-reyes",
    "jobTitle": "Infrastructure Engineer",
    "sameAs": ["https://github.com/danareyes"]
  }
}

Reference

3 pt

No machine-readable published or modified date

datePublished is present but dateModified is not, so freshness cannot be judged.

Why it matters. Answer engines prefer recent sources for questions about current state and use `dateModified` to decide whether a cached copy needs refetching. With no machine-readable date the page is treated as undated and loses to competitors that publish one.
Fix. Publish `datePublished` and `dateModified` in the page's structured data as ISO 8601 values with a timezone offset. Update `dateModified` only when the content actually changes, since bumping it on every deploy trains crawlers to ignore it. Mirror the value in a visible `<time datetime>` element so the rendered text and the metadata agree, and keep the sitemap `lastmod` consistent with it.

<time datetime="2026-08-04T14:20:00-04:00">Updated August 4, 2026</time>

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Article",
  "headline": "Allow AI answer engines in robots.txt",
  "datePublished": "2026-02-11T09:00:00-05:00",
  "dateModified": "2026-08-04T14:20:00-04:00"
}
</script>

Reference

3 pt

No Organization entity identifies the publisher

Organization entity present but no sameAs links to reconcile the entity.

Why it matters. An `Organization` node with `sameAs` links resolves your site to a single entity across knowledge graphs instead of leaving the publisher name as an ambiguous string. That resolution is what lets an assistant attribute an answer to your brand and reuse your name, logo, and contact details.
Fix. Publish one `Organization` node, usually on the home page, with `name`, `url`, `logo`, and `sameAs` pointing at the profiles that already describe you: Wikipedia or Wikidata, Crunchbase, LinkedIn, and your primary social accounts. Give it a stable `@id` such as `https://example.com/#organization` and reference that `@id` from each page's `publisher` property instead of repeating the block. Add `contactPoint` and `address` when they are public, and keep every value identical to what the site shows.

{
  "@context": "https://schema.org",
  "@type": "Organization",
  "@id": "https://example.com/#organization",
  "name": "Example",
  "legalName": "Example Holdings, Inc.",
  "url": "https://example.com",
  "logo": {
    "@type": "ImageObject",
    "url": "https://example.com/logo.png",
    "width": 512,
    "height": 512
  },
  "sameAs": [
    "https://www.wikidata.org/wiki/Q00000000",
    "https://www.linkedin.com/company/example",
    "https://github.com/example"
  ],
  "contactPoint": {
    "@type": "ContactPoint",
    "contactType": "customer support",
    "email": "support@example.com",
    "areaServed": "US",
    "availableLanguage": ["en"]
  }
}

Reference

3 pt

No machine-readable license or usage terms for the content

No licence declaration, so reuse terms are ambiguous.

Why it matters. A `license` property, or a linked terms page, states the reuse conditions in a place a crawler can read, rather than leaving them to be inferred. Where terms are unstated, some pipelines default to the more restrictive handling, which reduces how much of the text is quoted.
Fix. Add a `license` property to the page's structured data pointing at a specific license URL, such as a Creative Commons deed or your own terms page, and add `rel="license"` on the visible link. Use `usageInfo` for conditions that are not a standard license, such as attribution wording or an API-only clause. State the terms once, at a stable URL, and reference it from every page rather than restating it per template.

<a rel="license" href="https://creativecommons.org/licenses/by/4.0/">CC BY 4.0</a>

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Article",
  "headline": "Allow AI answer engines in robots.txt",
  "license": "https://creativecommons.org/licenses/by/4.0/",
  "usageInfo": "https://example.com/legal/content-reuse",
  "creditText": "Example, crawlcensus research desk"
}
</script>

Reference

2 pt

Evidence raw measurements

robots.txt

Size: 8,922 bytes
Groups: 4
Sitemaps: https://slate.com/sitemaps/sitemap-index.xml

View the file as our crawler received it

User-agent: *
Disallow: /search
Disallow: /comments/
Disallow: /_

Sitemap: https://slate.com/sitemaps/sitemap-index.xml

User-agent: AmazonAdBot
User-agent: Amazon-Advertising-ad-standards-bot
Allow: /

# Known agents

# AI Data Scraper, Scraper
User-agent: 008
User-agent: AdsTxtCrawler
User-agent: AI2Bot
User-agent: Ai2Bot-Dolma
User-agent: Amazonbot
User-agent: Applebot-Extended
User-agent: bedrockbot
User-agent: Bytespider
User-agent: CCBot
User-agent: ChatGLM-Spider
User-agent: ClaudeBot
User-agent: CloudVertexBot
User-agent: cohere-training-data-crawler
User-agent: CohereBot
User-agent: Cotoyogi
User-agent: Dataprovider.com
User-agent: Datenbank Crawler
User-agent: dcrawl
User-agent: DeepSeekBot
User-agent: Doubaobot
User-agent: ERNIEBot
User-agent: FacebookBot
User-agent: Google-Extended
User-agent: GoogleOther
User-agent: GPTBot
User-agent: HelloworkJobPostingBot
User-agent: HTTrack
User-agent: HTTrack 3.0
User-agent: ICC-Crawler
User-agent: imageSpider
User-agent: IndeedJobBot
User-agent: Kangaroo Bot
User-agent: KimiBot
User-agent: KimiCrawler
User-agent: KrawlerBot
User-agent: laion-huggingface-processor
User-agent: LCC
User-agent: meta-externalagent
User-agent: MetaInspector
User-agent: MetaJobBot
User-agent: micro-crawl
User-agent: MistralBot
User-agent: MoonshotBot
User-agent: MoonSpider
User-agent: netEstate Imprint Crawler
User-agent: newspaper
User-agent: Nutch
User-agent: nyt_scraping
User-agent: Offline Explorer
User-agent: omgili
User-agent: OpenindexSpider
User-agent: PanguBot
User-agent: Potions
User-agent: QwenBot
User-agent: SalamandraVLM
User-agent: SBIntuitionsBot
User-agent: Scrapy
User-agent: ServerHunterSpider
User-agent: Spider
User-agent: StatsDroneBot
User-agent: Thinkbot
User-agent: Timpibot
User-agent: VelenPublicWebCrawler
User-agent: webzio-extended
Disallow: /

# Intelligence Gatherer, SEO Crawler
User-agent: A360-Search
User-agent: aa
User-agent: ActiveComply
User-agent: Adagiobot
User-agent: adbeat_bot
User-agent: adidxbot
User-agent: AdkernelTopicCrawler
User-agent: admantx
User-agent: AdmixerBot
User-agent: AdsBot-Google
User-agent: AdsBot-Google-Mobile
User-agent: AffsignalCrawler
User-agent: Ahrefs Site Audit
User-agent: AhrefsBot
User-agent: AhrefsSiteAudit
User-agent: aiHitBot
User-agent: Amazing-SearchBot
User-agent: AmazingTest-SearchBot
User-agent: Amazon AdBot
User-agent: AmazonProductDiscovery
User-agent: AndersPinkBot
User-agent: ArchiveBot
User-agent: Assaybot
User-agent: Attracta
User-agent: AudigentAdBot
User-agent: Audisto Crawler
User-agent: Automattic Analytics Crawler
User-agent: Awario
User-agent: AwarioBot
User-agent: AwarioSmartBot
User-agent: Barkrowler
User-agent: BigUpDataBot
User-agent: Bing Ads
User-agent: BitSightBot
User-agent: Blackboard
User-agent: BLEXBot
User-agent: BomboraBot
User-agent: botify
User-agent: BrandVerity
User-agent: BrightEdge Bot
User-agent: BrightEdge Crawler
User-agent: Buck
User-agent: CaliberBot
User-agent: Caliperbot
User-agent: channable
User-agent: CheckMarkNetwork
User-agent: Cincraw
User-agent: ClarityBot
User-agent: Clearscopebot
User-agent: Clickagy Intelligence Bot
User-agent: Clickagy Intelligence Bot v2
User-agent: Cloudflare Custom Hostname Verification
User-agent: Cloudflare Stream Webhook
User-agent: Cloudflare-Healthchecks
User-agent: CloudFlare-Prefetch
User-agent: Cloudflare-SSLDetector
User-agent: Cloudflare-Traffic-Manager
User-agent: Cloudtrellis
User-agent: cludo.com
User-agent: Cocolyzebot
User-agent: cognitiveSEO Crawler
User-agent: contentking
User-agent: ContextualBot
User-agent: contxbot
User-agent: Convermax
User-agent: CriteoBot
User-agent: Cxense
User-agent: cXensebot
User-agent: DataForSEO
User-agent: DataForSEO Bot
User-agent: DataForSeoBot
User-agent: deepcrawl
User-agent: deepcrawl.com
User-agent: DomainStatsBot
User-agent: DotBot
User-agent: Dragonbot
User-agent: Dragonfly
User-agent: ds9
User-agent: DVbot
User-agent: Echobot Bot
User-agent: EcoVadisSustainabilityBot
User-agent: EpivozCrawler
User-agent: ev-crawler
User-agent: EzLynx
User-agent: EzoicBot
User-agent: EzoicBot-Nicheiq
User-agent: factset_spyderbot
User-agent: FDL Stats Bot
User-agent: Fedicabot
User-agent: Google AdsBot
User-agent: Google AdSense
User-agent: Google Digital Asset Links
User-agent: Google StoreBot
User-agent: Google-adstxt
User-agent: Google-Adwords-Instant
User-agent: Google-Display-Ads-Bot
User-agent: Google-Structured-Data-Testing
User-agent: GrapeshotCrawler
User-agent: GroovinaAdsbot
User-agent: HubSpot
User-agent: Huckabot
User-agent: Huckabuy Bot
User-agent: hypestat
User-agent: IAS crawler
User-agent: ias-ie
User-agent: IDG/IT
User-agent: ImagesiftBot
User-agent: Innguma
User-agent: InteractiveAdvertisingBureau
User-agent: IonCrawl
User-agent: James BOT
User-agent: Jugendschutzprogramm-Crawler
User-agent: KargoBot
User-agent: KargoBot-Artemis-Mobile
User-agent: Klaviyo
User-agent: KStandBot
User-agent: Leikibot
User-agent: LibreCrawl
User-agent: LightspeedSystemsCrawler
User-agent: LinkCheck by Siteimprove
User-agent: LinkChecker Bot
User-agent: linkchecker.pro
User-agent: LinkCheckerBot
User-agent: linkdexbot
User-agent: linkfluence
User-agent: LinksIndexerBot
User-agent: LinkWalker
User-agent: Macrobondbot
User-agent: magpie-crawler
User-agent: Mantisbot
User-agent: MarketGoo
User-agent: MBCrawler
User-agent: McontextualBot
User-agent: mediaboardbot
User-agent: MedialogiaBot
User-agent: MediaMonitoringBot
User-agent: Mediapartners-Google
User-agent: Mediatoolkitbot
User-agent: Mediavine Medatada Parser
User-agent: MediavineMetadataParser
User-agent: MegaIndex.ru
User-agent: meta-externalads
User-agent: MgidBot
User-agent: Missinglettr Bot
User-agent: MixrankBot
User-agent: MJ12bot
User-agent: ModernizeBot
User-agent: Moz dotbot
User-agent: Moz rogerbot
User-agent: MuckRack
User-agent: NanoInteractive
User-agent: Netcraft
User-agent: NetcraftSurveyAgent
User-agent: netEstate NE Crawler
User-agent: Neticle Crawler
User-agent: NetSeer crawler
User-agent: Netvibes
User-agent: Neu

Machine-readable extras

llms.txt: absent
ai.txt: absent
Sitemap: https://slate.com/sitemaps/sitemap-index.xml
Feeds: none
Schema types: NewsArticle, Organization, ImageObject, WebPageElement
Edge: Cloudflare
Final URL: https://slate.com/
HTML size: 470 KB, 1,695 words of text

Publish the score free

Sites that score well embed the badge. It links back to this live report, which re-measures on every scan.

<a href="https://crawlcensus.com/site/slate.com"><img src="https://crawlcensus.com/badge/slate.com.svg" alt="AI access score for slate.com" width="150" height="20"></a>

Track changes on this domain pro

Crawler policy is edited quietly. We re-scan monitored domains daily, keep the history, and email you the moment a crawler is blocked or unblocked, an llms.txt appears, or the score moves.

One address, unlimited domains during the beta. No newsletter, only change alerts.