Viziquo checks the root-level technical signals that help search and AI systems access and discover your public website. It verifies robots.txt, tests selected search crawlers, AI crawlers, and retrieval agents, follows your sitemap discovery path, and evaluates llms.txt and llms-full.txt when available.
Each result retains the technical evidence behind its pass, warning, or failure so your team can see what was tested and decide what requires action.
Technical Readiness focuses on controls and files that operate at the website level. It answers whether the site presents an observable root-level access or discovery barrier before your team investigates individual URLs.
Viziquo analyzes webpages separately in Page Analysis. Keeping the two workspaces distinct prevents a healthy root configuration from concealing problems on a specific page—and prevents one page-level issue from being mistaken for a site-wide failure.
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A current pass, warning, or fail status for robots.txt, the sitemap, and llms.txt, together with the date of the latest check.
Which site-level signals are healthy, which require review, and whether an observed condition affects crawler permission, URL discovery, or an optional AI-oriented guide. Each status leads to the underlying check evidence rather than an opaque composite score.
Root-level files serve different purposes and should not be treated as interchangeable. The summary helps teams distinguish an access restriction from a sitemap problem or a non-blocking llms.txt warning before deciding what to investigate.
Whether robots.txt exists, can be reached and parsed, declares a sitemap, imposes a global crawl block, and permits the selected user agents at the site root. The crawler view reports individual results for Googlebot, Bingbot, GPTBot, ChatGPT-User, ClaudeBot, Claude-User, and PerplexityBot.
Whether public content is being broadly restricted through root-level robots directives and whether a particular tested search crawler, AI crawler, or answer-time retrieval agent is allowed or blocked. Evidence includes the file URL, HTTP result, redirects, and parsed directives.
If a crawler cannot access the site, content improvements alone will not remove that access barrier. Crawler-specific results also prevent teams from assuming that one directive applies identically to search indexing, AI crawling, and answer-time retrieval.
Whether a sitemap was discovered, where it was found, whether it could be fetched and parsed, how many sitemap files were resolved, and how many unique URLs were identified. Recorded issues remain attached to the sitemap result.
Whether crawlers have a working discovery path to the site’s declared public URL inventory and whether the sitemap itself contains technical problems that deserve investigation.
A valid sitemap does not guarantee that every URL will be indexed or used in an AI answer, but it gives crawlers a structured inventory to discover. It also establishes a practical URL set for Page Analysis and can reveal when important public pages are absent from the declared inventory.
Whether root-level llms.txt and llms-full.txt files exist and can be read. When llms.txt is available, Viziquo examines its title and summary structure, sections, internal and external links, optional section, and invalid references.
Whether the site offers a usable AI-oriented guide to important public content. When the file is absent, Viziquo records that absence as a warning rather than presenting it as proof of blocked crawler access.
Teams can make an informed decision about publishing or improving an AI-oriented content map without mistaking an optional convention for a prerequisite to AI visibility. llms.txt complements accessible webpages, robots.txt, and sitemaps; it does not replace them.
A pass means the tested site-level barrier was not detected at the time of the check. It does not guarantee that an AI assistant will retrieve, cite, frame favorably, or recommend the brand.
Warnings also differ in consequence. A missing llms.txt guide is not equivalent to a global robots block or an inaccessible sitemap. Viziquo keeps the status, check category, URL, and supporting evidence visible so your team can evaluate the finding before changing the site.
Technical Readiness establishes whether root-level access and discovery controls are working. Page Analysis then evaluates the individual URLs in the discovered inventory for fetchability, bot protection, crawler access, indexability, canonicals, extractable content, metadata, and structured data.
The broader Viziquo analysis connects those technical findings to observed buyer conversations:
Visibility Analysis shows where the brand appeared, disappeared, or was displaced.
Brand Framing examines how AI assistants described and positioned the brand.
Recommendations connects reviewed findings to defensible strategic responses.
Tasks turns selected responses into implementation-ready work.
Evidence retains the conversations, citations, and retrieved search results behind the analysis.
Trends shows how visibility and citation patterns move across completed analyses.
Page Analysis evaluates individual URLs for fetchability, bot protection, crawler access, indexability, canonicals, extractable content, metadata, and structured data.
Yes. The current crawler-access view checks GPTBot, ChatGPT-User, ClaudeBot, Claude-User, and PerplexityBot, alongside Googlebot and Bingbot. Results are reported individually because robots directives can differ by user agent.
Viziquo keeps the categories visible because they represent different access paths. AI crawlers can collect public web content for model-related systems, while retrieval agents can request webpages when an assistant responds to a user. Permission for one user agent does not establish permission for another.
No. It means the tested robots directives did not block that user agent at the evaluated location. Discovery, retrieval, citation, and recommendation also depend on relevance, authority, source availability, provider behavior, and buyer context.
No. A valid sitemap supplies a structured discovery path. It does not require a search engine or AI system to index, retrieve, cite, or recommend every listed URL.
Viziquo records a missing llms.txt file as a warning, not as proof that AI crawlers or retrieval agents are blocked. It is evaluated as an optional AI-oriented guide alongside—not instead of—robots.txt, sitemaps, and accessible webpages.
Individual URLs are evaluated in the separate Page Analysis workspace. Technical Readiness focuses on site-level files and access controls; Page Analysis covers fetchability, page-specific crawler access, indexability, canonicals, content extraction, metadata, and structured data.
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Full Viziquo analyses include ChatGPT, Claude, Gemini, and Perplexity.
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