AI access report

nix.ru

Open to answer engines, no structured data.

9 failing 1 partial 17 passing Scanned 3 hours ago · 1 scan on record

Reach

40 / 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

21 / 25

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

Structure

7 / 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 / 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	allowed	not probed
OAI-SearchBot Indexes pages so they can be surfaced and cited in ChatGPT search results, not for training.	OpenAI	Answer index	allowed	not probed
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	allowed	not probed
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	allowed	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	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	not probed
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	allowed	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	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	allowed	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 40 / 40

✓

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

✓

Training crawlers may fetch this path

All 23 tracked training crawlers are allowed.

8 pt

✓

AI user agents receive the same 200 response as browsers

Live requests as 4 AI user agents were served normally.

6 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, 71935 bytes, 4 group(s).

3 pt

✓

No Crawl-delay directive constrains fetchers

No Crawl-delay directive.

2 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 21 / 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.

<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>

Reference

3 pt

✗

No lang attribute declares the document language

No lang attribute on <html>.

Why it matters. `<html lang>` tells tokenizers and language filters which language the text is in. Without it a retrieval pipeline guesses, and a wrong guess drops the page from language-scoped candidate sets and degrades sentence splitting.
Fix. Set a valid BCP 47 tag on the root element, such as `lang="en"` or `lang="pt-BR"`. Mark inline passages in another language with `lang` on the containing element. If you publish translations, pair the declaration with `hreflang` alternates so each version is attributed to the right locale.

<html lang="en">
  <head>
    <link rel="alternate" hreflang="es" href="https://example.com/es/page" />
  </head>
</html>

Reference

1 pt

✓

Substantive text is present in the server-rendered HTML

2678 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 25.0% of the 163 KB document; 5 KB is inline script.

4 pt

✓

Headings form a single, ordered outline

1 H1 and 25 headings total, 1 phrased as questions.

3 pt

✓

Title is unique and describes the page in specific terms

Title is 31 characters: "�� - �� "

3 pt

✓

Meta description provides an author-written summary

Meta description is 238 characters.

2 pt

Structure 7 / 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.

{
  "@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
    }
  }
}

Reference

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.

{
  "@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" }
      ]
    }
  ]
}

Reference

4 pt

✗

No reachable XML sitemap is declared

No sitemap.xml and none declared in robots.txt.

Why it matters. A sitemap gives crawlers the URL list and `lastmod` timestamps directly, instead of leaving discovery to link traversal that never reaches pages behind search forms or JavaScript routers. Fetchers use `lastmod` to prioritise recrawls, so fresh content is picked up sooner.
Fix. Publish a sitemap of canonical, indexable URLs and reference it with an absolute `Sitemap:` line in robots.txt. Keep each file under 50,000 URLs and 50 MiB uncompressed, using a sitemap index when you exceed either limit. Set `lastmod` from real content changes rather than the build clock, and exclude redirects, error pages, and non-canonical variants.

<?xml version="1.0" encoding="UTF-8"?>
<urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9">
  <url>
    <loc>https://example.com/blog/robots-for-ai</loc>
    <lastmod>2026-08-04T14:20:00-04:00</lastmod>
  </url>
</urlset>

Reference

2 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://www.nix.ru/

3 pt

✓

Key facts are available in lists or tables

5 tables, 21 lists, 0 code blocks, 1 question headings.

1 pt

Attribution 1 / 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

No publication or modification dates in structured data.

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

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.

{
  "@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: 71,935 bytes
Groups: 4
Sitemaps: none declared

View the file as our crawler received it

User-agent: *
Disallow: /abc3/

Disallow: /3d_mouse
Disallow: /acc_tripods
Disallow: /accessory_apple
Disallow: /accessory_samsung
Disallow: /accompanying_articles
Disallow: /accupractic_accurack
Disallow: /acer/acer_notebook
Disallow: /action_cam
Disallow: /adapters_switches
Disallow: /adda/coolers
Disallow: /air_filters
Disallow: /albatron/svga_albatron
Disallow: /amd
Disallow: /amortizatory_torr
Disallow: /antiviruses
Disallow: /apc
Disallow: /apple_notebook
Disallow: /arctic_cooling
Disallow: /asus/asus_notebook
Disallow: /asus/asustek_coolers
Disallow: /asus/asustek_video
Disallow: /asus_computers
Disallow: /asus_sound
Disallow: /ati
Disallow: /audiocables_audioadapters
Disallow: /aureal_sound
Disallow: /auto_battery
Disallow: /auto_power_supplies
Disallow: /autodesk
Disallow: /avtoehlektrika
Disallow: /avtogadzhety
Disallow: /avtoinstrument_other
Disallow: /avtokresla
Disallow: /avtomagnitoly
Disallow: /avtomaticheskie_vykljuchateli
Disallow: /avtomobilnye-kolonki
Disallow: /avtoprinadlejnosti
Disallow: /baby_carriages
Disallow: /baby_feeding
Disallow: /babycare
Disallow: /barcode_scanners
Disallow: /barebone
Disallow: /bathroom_scales_bosch
Disallow: /bathroom_scales_galaxy
Disallow: /bathroom_scales_others
Disallow: /bathroom_scales_polaris
Disallow: /bathroom_scales_scarlett
Disallow: /bathroom_scales_sinbo
Disallow: /bathroom_scales_supra
Disallow: /bathroom_scales_tefal
Disallow: /batteries
Disallow: /batteries_for_cordless
Disallow: /batteries_for_notebook
Disallow: /batteries_for_ups
Disallow: /beauty_and_personal_care
Disallow: /beauty_and_personal_care_galaxy
Disallow: /Behringer_sound
Disallow: /belinea
Disallow: /bfg
Disallow: /binocular
Disallow: /BlackAndDecker_Chain_Saw
Disallow: /BlackAndDecker_Drill
Disallow: /BlackAndDecker_Grinder
Disallow: /BlackAndDecker_lawn-mower
Disallow: /BlackAndDecker_other_tools
Disallow: /BlackAndDecker_planer
Disallow: /BlackAndDecker_Rotary_Hammer
Disallow: /BlackAndDecker_Router
Disallow: /BlackAndDecker_sander
Disallow: /BlackAndDecker_saw
Disallow: /BlackAndDecker_Screwdriver
Disallow: /blenders_bosch
Disallow: /blenders_braun
Disallow: /blenders_electrolux
Disallow: /blenders_galaxy
Disallow: /blenders_gorenje
Disallow: /blenders_kitfort
Disallow: /blenders_moulinex
Disallow: /blenders_other
Disallow: /blenders_panasonic
Disallow: /blenders_philips
Disallow: /blenders_polaris
Disallow: /blenders_redmond
Disallow: /blenders_scarlett
Disallow: /blenders_sinbo
Disallow: /bliss_notebook
Disallow: /bloki_lazera_skanera
Disallow: /bloki_proyavki
Disallow: /blu_ray
Disallow: /blu_ray_disks
Disallow: /boilers_ariston
Disallow: /boilers_de_luxe
Disallow: /boilers_electrolux
Disallow: /boilers_gorenje
Disallow: /boilers_haier
Disallow: /boilers_hyundai
Disallow: /boilers_oasis
Disallow: /boilers_other
Disallow: /boilers_polaris
Disallow: /boilers_stiebel_eltron
Disallow: /boilers_thermex
Disallow: /boilers_timberk
Disallow: /Bort_Drill
Disallow: /Bort_Grinder
Disallow: /Bort_HeatGun
Disallow: /bort_other_tools
Disallow: /Bort_Planer
Disallow: /Bort_Rotary_Hammer
Disallow: /Bort_sander
Disallow: /Bort_Saw
Disallow: /Bort_Screwdriver
Disallow: /Bosch_blade
Disallow: /Bosch_Chain_Saw
Disallow: /Bosch_Drill
Disallow: /Bosch_Grinder
Disallow: /Bosch_HeatGun
Disallow: /Bosch_High_Pressure_Cleaner
Disallow: /Bosch_lawn-mower
Disallow: /bosch_other_tools
Disallow: /Bosch_Planer
Disallow: /Bosch_Rotary_Hammer
Disallow: /Bosch_Router
Disallow: /Bosch_sander
Disallow: /Bosch_Saw
Disallow: /Bosch_Screwdriver
Disallow: /brake_shoes
Disallow: /brake_shoes_and_disks_blitz
Disallow: /brother
Disallow: /burocrat/stationery
Disallow: /business_literature
Disallow: /business_software
Disallow: /cable_channel
Disallow: /cable_laying
Disallow: /cable_management
Disallow: /cables
Disallow: /cables_lightning
Disallow: /calculators
Disallow: /calibrators
Disallow: /camera_bags
Disallow: /camera_bags_case_logic
Disallow: /camera_bags_lowepro
Disallow: /camera_bags_tamrac
Disallow: /cameras_premier
Disallow: /canon/faxes
Disallow: /canon_acc
Disallow: /canon_copiers
Disallow: /card_readers
Disallow: /car-lights
Disallow: /cartridges_qumo
Disallow: /cartridges_sakura
Disallow: /cartriges
Disallow: /cases
Disallow: /cases_1stplayer
Disallow: /cases_3q
Disallow: /cases_3r
Disallow: /cases_aerocool
Disallow: /cases_antec
Disallow: /cases_aopen
Disallow: /cases_ascot
Disallow: /cases_asus
Disallow: /cases_atx
Disallow: /cases_be_quiet
Disallow: /cases_BitFenix
Disallow: /cases_chieftec
Disallow: /cases_classix
Disallow: /cases_codegen
Disallow: /cases_colors
Disallow: /cases_coolermaster
Disallow: /cases_corsair
Disallow: /cases_crown
Disallow: /cases_deepcool
Disallow: /cases_delux
Disallow: /cases_espada
Disallow: /cases_exegate
Disallow: /cases_fox
Disallow: /cases_foxconn
Disallow: /cases_Fractal_Design
Disallow: /cases_frontier
Disallow: /cases_gamemax
Disallow: /cases_gembird
Disallow: /cases_gigabyte
Disallow: /cases_ginzzu
Disallow: /cases_gmc
Disallow: /cases_hiper
Disallow: /cases_hkc
Disallow: /cases_ikonik
Disallow: /cases_intel
Disallow: /cases_inwin
Disallow: /cases_jonsbro
Disallow: /cases_lian_li
Disallow: /cases_linkworld
Disallow: /cases_microlab
Disallow: /cases_microtech
Disallow: /cases_Morex
Disallow: /cases_MSI
Disallow: /cases_navan
Disallow: /cases_navipower
Disallow: /cases_NZXT
Disallow: /cases_optimum
Disallow: /cases_phanteks
Disallow: /cases_powercase
Disallow: /cases_powercool
Disallow: /cases_powerman
Disallow: /cases_procase
Disallow: /cases_raidmax
Disallow: /cases_rl
Disallow: /cases_sigma
Disallow: /cases_silver_stone
Disallow: /cases_simplex
Disallow: /cases_storm
Disallow: /cases_superflower
Disallow: /cases_supermicro
Disallow: /cases_thermaltake
Disallow: /cases_trin
Disallow: /cases_tsunami
Disallow: /cases_winard_qori
Disallow: /cases_zalman
Disallow: /cases_Zignum
Disallow: /cd_bags
Disallow: /cd_mp3_player_iriver
Disallow: /cd_mp3_player_nexx
Disallow: /cd_mp3_player_orient
Disallow: /cd_mp3_player_panasonic
Disallow: /cd_mp3_pl

Machine-readable extras

llms.txt: absent
ai.txt: absent
Sitemap: absent
Feeds: none
Schema types: none
Edge: not identified
Final URL: https://www.nix.ru/
HTML size: 163 KB, 2,678 words of text

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