rhw.one scored 35/100 on the Prominara AI Visibility Index, which represents a score that indicates significant opportunities for improvement, as the site currently lacks many of the signals that AI search engines look for when selecting sources to cite. This analysis runs over 40 page- and site-level checks across four key categories: content structure, entity and topic coverage, authority signals, and technical readiness. The score reflects how likely AI search engines like ChatGPT, Perplexity, and Google AI are to discover, understand, and cite content from rhw.one in their responses.

The score measures this page against the checks, not against other sites. The current rating of “Needs Work” means prioritizing the critical recommendations below will yield the most significant improvements in AI search visibility.

An AI visibility score measures how likely a website is to appear in and be cited by AI-powered search engines and assistants. As AI tools like ChatGPT, Perplexity, Google AI Overviews, and Claude become primary information sources for millions of users, traditional SEO alone is no longer sufficient. Generative Engine Optimization (GEO) is the practice of optimizing content specifically for these AI systems.

Unlike traditional search engines that rank pages in a list, AI search engines synthesize information from multiple sources into a single response. Being cited in these responses requires content that is factually accurate, well-structured, authoritative, and technically accessible to AI crawlers. The AI visibility score quantifies how well a page meets these requirements across the four key categories that AI systems evaluate when selecting sources.

A high AI visibility score correlates with increased brand mentions in AI-generated responses, improved organic reach through AI search platforms, and stronger positioning as a trusted source in your industry. Regular monitoring and optimization of AI visibility factors ensures that your content remains competitive as AI search continues to evolve.

The Prominara AI Visibility Score is calculated from over 40 page- and site-level checks grouped into four weighted categories: Content Structure (30%), Entity & Topics (25%), Authority Signals (15%), and Technical Readiness (30%). Each check is tied to published research on what AI engines cite; checks without supporting evidence (such as llms.txt, FAQ blocks or word count) are reported but do not move the score.

Technical Readiness and Content Structure carry the most weight because the evidence is strongest there: an engine has to reach and read the page, then find a passage it can quote. A page that blocks AI search crawlers or is set to noindex is capped at 40, and a page whose main content only appears after JavaScript runs is capped at 50, however good the content is. A nosnippet or max-snippet:0 caps only the Google AI Overviews / AI Mode scores at 40, since Google and Bing are the engines that document honoring it.

Scores range from 0 to 100: 80 and above is rated Excellent, 60 to 79 Good, 40 to 59 Fair, and below 40 Needs Work. A higher score means fewer of the checked gaps remain on the page.

GPTBot is OpenAI's model-training crawler. Blocking it is a content-licensing choice — it does not remove your site from ChatGPT's answers. ChatGPT Search visibility depends on OAI-SearchBot and on being indexed in Bing (Bingbot). Keep those two allowed in robots.txt; decide about GPTBot separately based on your training-data policy.

PerplexityBot is Perplexity AI's crawler. Perplexity is a citation-first AI search engine, meaning it explicitly links to the sources it quotes. Allowing PerplexityBot is a prerequisite for being cited; content freshness, factual density, and unique first-party data strongly influence citation likelihood.

Google-Extended is a robots.txt token that controls whether Google may use a site's content to train Gemini models. It does not control AI Overviews or AI Mode — those are built from Google's regular search index, crawled by Googlebot. Blocking Google-Extended opts a site out of Gemini training with no effect on Search rankings or AI Overviews; blocking Googlebot is what removes a site from both.

E-E-A-T stands for Experience, Expertise, Authoritativeness, and Trustworthiness. Originally a Google search quality framework, E-E-A-T is now a leading proxy for how AI systems evaluate source credibility. Strong signals include clear author attribution with credentials, publication and last-updated dates, citations to authoritative sources, transparent methodology, and Schema.org structured data.

llms.txt is an emerging standard that lets site owners publish a machine-readable map of their most important content for large language models. Placed at /llms.txt, it mirrors the spirit of robots.txt and sitemap.xml but is optimized for LLM consumption: concise descriptions, canonical URLs, and priority hints. Adoption is growing across AI platforms.