AI access report
leofame.com
Blocks 1 of 24 answer engines, blocks 4 training crawlers, refuses AI user agents at the edge, no structured data.
6 failing
3 partial
16 passing
Scanned 1 hour ago · 4 scans on record
trend
Reach
22.8
/ 40
Whether AI crawlers and answer-engine fetchers are permitted to request the page at all. What happens on the wire outweighs what the policy file says: a live refusal costs 16 of these 40 points, twice what the heaviest robots.txt rule costs, because a page a crawler cannot fetch is unreadable no matter how well it is marked up.
Readability
22
/ 25
Whether a fetcher that does not execute JavaScript receives the actual content, in markup an extractor can segment.
Structure
9
/ 20
Machine-readable markup that states the page's type, entities, canonical URL, and discrete facts instead of leaving them to be inferred.
Attribution
1
/ 9
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 1 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 403 |
| OAI-SearchBot Indexes pages so they can be surfaced and cited in ChatGPT search results, not for training. |
OpenAI | Answer index | allowed | refused 403 |
| 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 | blocked Disallow: / |
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 | allowed | refused 403 |
| 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. |
Model training | blocked Disallow: / |
not probed | |
| Googlebot Crawls and renders pages for Google Search, Images, Video, News and Discover. |
Answer index | allowed | not probed | |
| Googlebot-News Robots token controlling Google News inclusion; crawling itself uses the Googlebot user agents. |
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. |
Live retrieval | allowed | not probed | |
| GoogleOther Generic Google crawler used by product teams for one-off fetches such as internal research and development. |
Model training | allowed | 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 | allowed | 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 403 |
| 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 | allowed | 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 | allowed | 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 | allowed | 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 | allowed | 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 | allowed | not probed |
| omgilibot Legacy Omgili search crawler token still blocked alongside the current omgili agent. |
Webz.io | Model training | allowed | 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 | allowed | 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 | allowed | 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 | allowed | not probed |
| Timpibot Crawls pages for Timpi's decentralized index, which is also used as LLM training data. |
Timpi | Model training | allowed | 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 | allowed | not probed |
| SemrushBot-OCOB Crawls pages to feed Semrush's ContentShake AI writing tool. |
Semrush | Model training | blocked Disallow: / |
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 22.8 / 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 403 Forbidden; HTTP 403 Forbidden; HTTP 403 Forbidden; HTTP 403 Forbidden).
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.
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"
done16 pt
!
Answer-engine fetchers are blocked, so you cannot be cited
Blocked from citing you: ChatGPT-User.
Why it matters. Retrieval fetchers (OAI-SearchBot, ChatGPT-User, Claude-User, Claude-SearchBot, PerplexityBot, Perplexity-User) load a page at answer time to quote and link it. When robots.txt disallows them the assistant drops the URL from its candidate set, so the citation goes to a competitor while your training exposure stays exactly the same.
Fix. Separate the two crawler classes in robots.txt instead of blocking by vendor. Allow `OAI-SearchBot` and `ChatGPT-User` (OpenAI retrieval and user-initiated fetches), `Claude-SearchBot` and `Claude-User` (Anthropic retrieval), and `PerplexityBot` and `Perplexity-User`; keep any opt-out you want on `GPTBot`, `ClaudeBot`, `CCBot`, `Google-Extended`, and `Applebot-Extended`. Order does not decide precedence in RFC 9309 parsers, the longest matching rule does, so make the allow rules at least as specific as the disallow rules. Blocking retrieval buys nothing on training, because the training crawlers are separate user agents with separate rules.
Fix. Separate the two crawler classes in robots.txt instead of blocking by vendor. Allow `OAI-SearchBot` and `ChatGPT-User` (OpenAI retrieval and user-initiated fetches), `Claude-SearchBot` and `Claude-User` (Anthropic retrieval), and `PerplexityBot` and `Perplexity-User`; keep any opt-out you want on `GPTBot`, `ClaudeBot`, `CCBot`, `Google-Extended`, and `Applebot-Extended`. Order does not decide precedence in RFC 9309 parsers, the longest matching rule does, so make the allow rules at least as specific as the disallow rules. Blocking retrieval buys nothing on training, because the training crawlers are separate user agents with separate rules.
# Retrieval and citation fetchers: allowed.
User-agent: OAI-SearchBot
User-agent: ChatGPT-User
User-agent: Claude-SearchBot
User-agent: Claude-User
User-agent: PerplexityBot
User-agent: Perplexity-User
Allow: /
# Training and dataset crawlers: disallowed.
User-agent: GPTBot
User-agent: ClaudeBot
User-agent: CCBot
User-agent: Google-Extended
User-agent: Applebot-Extended
Disallow: /
User-agent: *
Allow: /
Disallow: /checkout
Sitemap: https://example.com/sitemap.xml8 pt
!
Training crawlers are disallowed for this path
Blocked by robots.txt: GPTBot, Google-Extended, SemrushBot-OCOB, 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.
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: /5 pt
✓
No blanket disallow applies to this path
The wildcard group does not disallow the entire site.
4 pt
✓
robots.txt served as plain text with a 200 response
robots.txt served, 17589 bytes, 29 group(s).
2 pt
✓
Page is indexable, with no noindex directive
No noindex directive on the homepage.
2 pt
✓
No Crawl-delay directive constrains fetchers
No Crawl-delay directive.
1 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 22 / 25
✗
No <main> or <article> element marks the primary content
No <main> or <article> element, so extractors must guess where the content starts.
Why it matters. Boilerplate removers use `<main>` and `<article>` to decide which subtree is the content and which is navigation, promo, and footer. Without a landmark the extractor guesses by text density and often keeps the nav while dropping part of the body.
Fix. Wrap the page's unique content in exactly one `<main>` element, and use `<article>` for each self-contained item inside it. Put navigation in `<nav>`, site chrome in `<header>` and `<footer>`, and tangential blocks in `<aside>` so they are cleanly separable. Do not nest the content inside a `<div>` whose only meaning is a CSS class.
Fix. Wrap the page's unique content in exactly one `<main>` element, and use `<article>` for each self-contained item inside it. Put navigation in `<nav>`, site chrome in `<header>` and `<footer>`, and tangential blocks in `<aside>` so they are cleanly separable. Do not nest the content inside a `<div>` whose only meaning is a CSS class.
<body>
<header><nav><!-- site navigation --></nav></header>
<main>
<article>
<h1>How answer engines fetch your pages</h1>
<p>Content that should be extracted and quoted.</p>
</article>
</main>
<aside><!-- related links --></aside>
<footer><!-- legal, contact --></footer>
</body>3 pt
✓
Substantive text is present in the server-rendered HTML
930 words of text are present in the raw HTML. Most AI fetchers do not run JavaScript.
9 pt
✓
Visible text makes up a healthy share of the HTML payload
Text is 14.7% of the 40 KB document; 2 KB is inline script.
4 pt
✓
Headings form a single, ordered outline
1 H1 and 17 headings total, 2 phrased as questions.
3 pt
✓
Title is unique and describes the page in specific terms
Title is 61 characters: "Buy Instagram Followers and TikTok Growing Services - Leofame"
3 pt
✓
Meta description provides an author-written summary
Meta description is 162 characters.
2 pt
✓
Document language is declared on the html element
Declared language: en.
1 pt
Structure 9 / 20
✗
No JSON-LD structured data found on the page
No JSON-LD structured data on the homepage.
Why it matters. JSON-LD gives an answer engine typed facts (headline, author, dates, price, publisher) without inferring them from prose, and those fields populate the entity record a citation is attached to. With no structured data every attribute has to be guessed from text, and guesses are dropped when confidence is low.
Fix. Add one `<script type="application/ld+json">` block describing the page's primary entity, using the schema.org type that actually fits: `Article` or `NewsArticle`, `Product`, `Recipe`, `Event`, `FAQPage`, or `SoftwareApplication`. Populate the required properties for that type and make every value match visible page content. Prefer JSON-LD over microdata or RDFa, since it is the format the major crawlers document, and render it server-side so non-JavaScript fetchers see it.
Fix. Add one `<script type="application/ld+json">` block describing the page's primary entity, using the schema.org type that actually fits: `Article` or `NewsArticle`, `Product`, `Recipe`, `Event`, `FAQPage`, or `SoftwareApplication`. Populate the required properties for that type and make every value match visible page content. Prefer JSON-LD over microdata or RDFa, since it is the format the major crawlers document, and render it server-side so non-JavaScript fetchers see it.
{
"@context": "https://schema.org",
"@type": "Article",
"headline": "Allow AI answer engines in robots.txt",
"description": "How to opt out of model training while staying citable.",
"url": "https://example.com/blog/robots-for-ai",
"mainEntityOfPage": {
"@type": "WebPage",
"@id": "https://example.com/blog/robots-for-ai"
},
"image": "https://example.com/images/robots-for-ai.png",
"inLanguage": "en",
"datePublished": "2026-02-11T09:00:00-05:00",
"dateModified": "2026-08-04T14:20:00-04:00",
"author": {
"@type": "Person",
"name": "Dana Reyes",
"url": "https://example.com/authors/dana-reyes"
},
"publisher": {
"@type": "Organization",
"name": "Example",
"url": "https://example.com",
"logo": {
"@type": "ImageObject",
"url": "https://example.com/logo.png",
"width": 512,
"height": 512
}
}
}7 pt
✗
Structured data is too generic for what the page is about
No entity types that answer engines consume.
Why it matters. Answer engines route by entity type: a `Product` node supplies price and availability, an `Article` node supplies author and dates, and a `FAQPage` node supplies question and answer pairs. A generic `WebPage` or `WebSite` node on a product or article page carries none of those fields, so the specific facts stay unavailable.
Fix. Replace bare `WebPage` and `WebSite` nodes with the most specific type that describes the page, and fill the properties that type defines. Use `@graph` to publish several linked nodes on one page, such as an `Article` whose `publisher` points at an `Organization` node by `@id`. Add `BreadcrumbList` for hierarchy and reuse the same `@id` values across pages so the entity resolves to one record.
Fix. Replace bare `WebPage` and `WebSite` nodes with the most specific type that describes the page, and fill the properties that type defines. Use `@graph` to publish several linked nodes on one page, such as an `Article` whose `publisher` points at an `Organization` node by `@id`. Add `BreadcrumbList` for hierarchy and reuse the same `@id` values across pages so the entity resolves to one record.
{
"@context": "https://schema.org",
"@graph": [
{
"@type": "Product",
"@id": "https://example.com/products/widget#product",
"name": "Widget Pro",
"sku": "WGT-PRO-1",
"brand": { "@type": "Brand", "name": "Example" },
"offers": {
"@type": "Offer",
"url": "https://example.com/products/widget",
"price": "49.00",
"priceCurrency": "USD",
"availability": "https://schema.org/InStock"
}
},
{
"@type": "BreadcrumbList",
"itemListElement": [
{ "@type": "ListItem", "position": 1, "name": "Products", "item": "https://example.com/products" },
{ "@type": "ListItem", "position": 2, "name": "Widget Pro" }
]
}
]
}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://leofame.com/
3 pt
✓
XML sitemap is declared in robots.txt and returns 200
Sitemap found at /sitemap.xml (52 URLs on the first document).
2 pt
✓
Key facts are available in lists or tables
0 tables, 11 lists, 0 code blocks, 2 question headings.
1 pt
Attribution 1 / 9
✗
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.
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.4 pt
✗
No Organization entity identifies the publisher
No Organization entity, so the brand is harder to resolve to a known 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.
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"]
}
}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.
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>2 pt
–
No machine-readable author is attached to the page
This page declares no article-type structured data, so a machine-readable byline is not expected of it. The check is excluded from the score rather than counted as a failure.
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.
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"]
}
}3 pt
–
No machine-readable published or modified date
This page declares no article-type structured data, so publication and modification dates are not expected of it. The check is excluded from the score rather than counted as a failure.
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.
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>3 pt
Evidence raw measurements
robots.txt
- Size
- 17,589 bytes
- Groups
- 29
- Sitemaps
- https://leofame.com/sitemap.xml
View the file as our crawler received it
User-agent: Google-Extended
User-agent: GPTBot
User-agent: GPTBot-User
User-agent: ChatGPT
User-agent: 008
User-agent: 360Spider
User-agent: 404checker
User-agent: 404enemy
User-agent: 80legs
User-agent: 8484 Boston Project v 1.0
Disallow: /
User-agent: Amazonbot
Disallow: /do-not-crawl/
User-agent: Abonti
User-agent: Aboundex
User-agent: Accoona-AI-Agent
User-agent: Acunetix
User-agent: ADmantX
User-agent: AfD-Verbotsverfahren
User-agent: AhrefsBot
User-agent: AIBOT
User-agent: AiHitBot
User-agent: Aipbot
User-agent: Alexibot
User-agent: Alligator
User-agent: AllSubmitter
User-agent: AlphaBot
User-agent: AlvinetSpider
User-agent: Anarchie
User-agent: AnsearchBot
User-agent: AnsearchBot/1.0
User-agent: Anonymization.Net
User-agent: Anonymization.Net Vivaldi
User-agent: Antenne Hatena
User-agent: Apache-HttpClient
User-agent: Apexoo
User-agent: ApocalXExplorerBot
User-agent: Arachnophilia
User-agent: archive.org_bot
User-agent: ASPSeek
User-agent: Asterias
User-agent: ASpider/0.09
User-agent: Attach
User-agent: AURESYS/1.0
User-agent: autoemailspider
Disallow: /
User-agent: b2w/0.1
User-agent: BackDoorBot
User-agent: Backlink-Ceck
User-agent: backlink-check
User-agent: BacklinkCrawler
User-agent: BackRub/.
User-agent: BackStreet
User-agent: BackWeb
User-agent: Badass
User-agent: Baiduspider
User-agent: Baiduspider-favo
User-agent: Baiduspider-cpro
User-agent: Baiduspider-ads
User-agent: Baiduspider-news
User-agent: Baiduspider-video
User-agent: Baiduspider-image
User-agent: Bandit
User-agent: Barkrowler
User-agent: BatchFTP
User-agent: Battleztar Bazinga
User-agent: BaySpider
User-agent: BBBike
User-agent: BDCbot
User-agent: BDFetch
User-agent: BecomeBot/1.23
User-agent: BetaBot
User-agent: Bigfoot
User-agent: Bitacle
User-agent: Big Brother
User-agent: Bizbot003
User-agent: BizBot04 kirk.overleaf.com
User-agent: BizInformation
User-agent: Blackboard
User-agent: Black Hole
User-agent: BlackWidow
User-agent: BLEXBot
User-agent: Blow
User-agent: BlowFish
User-agent: Boardreader
User-agent: Bolt
User-agent: BotALot
User-agent: Brandprotect
User-agent: Brandwatch
User-agent: BSpider
User-agent: BSpider/1.0 libwww-perl/0.40
User-agent: Bubing
User-agent: Buddy
User-agent: BuiltBotTough
User-agent: BuiltWith
User-agent: Bullseye
User-agent: BunnySlippers
User-agent: BuzzSumo
Disallow: /
User-agent: Calculon
User-agent: Calif Univ Tools
User-agent: CATExplorador
User-agent: CazoodleBot
User-agent: CCBot
User-agent: Cegbfeieh
User-agent: Cerberian
User-agent: Check&Get
User-agent: CheeseBot
User-agent: CherryPicker
User-agent: CherryPickerElite
User-agent: CherryPickerElite/1.0
User-agent: CherryPickerSE
User-agent: CherryPickerSE/1.0
User-agent: ChinaClaw
User-agent: christcrawler
User-agent: Chlooe
User-agent: Claritybot
User-agent: Cliqzbot
User-agent: Cloud mapping
User-agent: coccocbot-web
User-agent: Cogentbot
User-agent: cognitiveseo
User-agent: Collector
User-agent: com.plumanalytics
User-agent: ConveraCrawler
User-agent: Copier
User-agent: CopyRightCheck
User-agent: Copyscape
User-agent: Cosmos
User-agent: Craftbot
User-agent: crawler4j
User-agent: crawler.feedback
User-agent: crawl.sogou.com
User-agent: CrazyWebCrawler
User-agent: Crescent
User-agent: Crescent Internet ToolPak HTTP OLE Control
User-agent: CSHttp
User-agent: Curious
User-agent: Custo
User-agent: CustomExchangeBrowser
Disallow: /
User-agent: DatabaseDriverMysqli
User-agent: DataCha0s
User-agent: DBLBot
User-agent: demandbase-bot
User-agent: Demon
User-agent: DepSpid
User-agent: Deusu
User-agent: Devil
User-agent: Digincore
User-agent: DigitalPebble
User-agent: DIIbot
User-agent: Dirbuster
User-agent: Disco
User-agent: Discobot
User-agent: DISCo Pump 3.1
User-agent: Discoverybot
User-agent: DittoSpyder
User-agent: DnyzBot
User-agent: DomainAppender
User-agent: DomainCrawler
User-agent: DomainSigmaCrawler
User-agent: DomainStatsBot
User-agent: Dotbot
User-agent: Download Wonder
User-agent: Dragonfly
User-agent: Drip
User-agent: DTS Agent
Disallow: /
User-agent: e-SocietyRobot
User-agent: EasyDL
User-agent: Ebingbong
User-agent: eCatch
User-agent: ECCP/1.0
User-agent: EchO!
User-agent: Ecxi
User-agent: edgeio-retriever
User-agent: EirGrabber
User-agent: EmailCollector
User-agent: EMail Siphon
User-agent: EMail Wolf
User-agent: EmailSiphon
User-agent: EmailWolf
User-agent: EnigmaBot
User-agent: Entrieva
User-agent: EroCrawler
User-agent: evc-batch
User-agent: Evil
User-agent: Exabot
User-agent: explorersearch
User-agent: Express WebPictures
User-agent: ExtLinksBot
User-agent: Extractor
User-agent: ExtractorPro
User-agent: Extreme Picture Finder
User-agent: EyeNetIE
User-agent: Ezooms
Disallow: /
User-agent: f-bot test pilot
User-agent: Factbot
User-agent: FDM
User-agent: FemtosearchBot
User-agent: FHscan
User-agent: Filangy
User-agent: Fimap
User-agent: findlinks
User-agent: Firefox/7.0
User-agent: Flamingo_SearchEngine
User-agent: FlashGet
User-agent: Flunky
User-agent: Foobot
User-agent: Franklin Locator 1.8
User-agent: Freeuploader
User-agent: FrontPage
User-agent: FurlBot
User-agent: Furl Search
User-agent: FyberSpider
User-agent: Fyrebot
Disallow: /
User-agent: GalaxyBot
User-agent: Genieo
User-agent: GermCrawler
User-agent: Getintent
User-agent: GetRight
User-agent: GetWeb
User-agent: Gigablast
User-agent: Gigabot
User-agent: G-i-g-a-b-o-t
User-agent: Girafabot
User-agent: Go-Ahead-Got-It
User-agent: Gotit
User-agent: GoZilla
User-agent: Go!Zilla
User-agent: gqbi hnxupsxgfgnX berXjteu
User-agent: Grabber
User-agent: GrabNet
User-agent: Grafula
User-agent: GrapeFX
User-agent: Green Research, Inc.
User-agent: GridBot
User-agent: GT::WWW
Disallow: /
User-agent: Haansoft
User-agent: HaosouSpider
User-agent: Harvest
User-agent: Harvest/1.5
User-agent: Havij
User-agent: HEADMasterSEO
User-agent: Heritrix
User-agent: Hloader
User-agent: HMView
User-agent: HTMLparser
User-agent: HTTP::Lite
User-agent: httplib
User-agent: HTTrack
User-agent: HTTrack 3.0
User-agent: Huaweisymantecspider
User-agent: Humanlinks
User-agent: Machine-readable extras
- llms.txt
- absent
- ai.txt
- absent
- Sitemap
- /sitemap.xml (52 URLs)
- Feeds
- none
- Schema types
- none
- Edge
- not identified
- Final URL
- https://leofame.com/
- HTML size
- 40 KB, 930 words of text
Compare it with a competitor head to head
Put leofame.com next to another domain and see which one an answer engine can actually read. Both sides are measured the same way, so the difference is the finding.
Already measured: vs orangeclickmedia.com · vs kapwing.com · vs xxxviijmp.com
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/leofame.com"><img src="https://crawlcensus.com/badge/leofame.com.svg" alt="AI access score for leofame.com" width="150" height="20"></a>Track changes on this domain free for one
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.
Free for one domain per address, and always free for domains you have verified you own. No newsletter, only change alerts.
Pro follows 25 domains, keeps 90 days of history, compares them against each other and exports the lot as CSV, for 19 dollars a month. That is the difference: measuring is free, watching a portfolio is not.