# AI Search > AISearch.wiki is an independent reference, diagnostic and monitoring site for AI search visibility. It separates technical AI search readiness, webpage visibility potential, and observed AI visibility, including competitor comparison across defined prompts and configured AI answer providers. Last verified: 2026-09-10. Canonical site: https://www.aisearch.wiki/ This root `llms.txt` covers all public URLs under `https://www.aisearch.wiki/`. ## Core Measurement Model AISearch.wiki intentionally distinguishes four related measurements: - **AI Search Readiness**: whether a public page is technically prepared to be discovered and interpreted. Typical signals include crawlability, indexability, canonicalization, sitemap discovery, crawler access, headings, structured data, authorship and visible sources. - **AI Visibility Potential**: whether a public page contains strong observable signals for discoverability, entity clarity, source-worthiness, answer extractability, trust and freshness. - **Observed AI Visibility**: whether a target brand or domain actually appears, is mentioned or is cited for a defined prompt set at a defined time across configured AI answer providers. - **Competitor Comparison**: comparison of the target and explicitly tracked competitors using the same prompt set and observation framework, including mention coverage, domain citations and approximate share of voice within the tracked set. Readiness and visibility-potential scores do not guarantee observed mentions or citations. Observed results are also not permanent rankings; they may vary by platform, prompt, locale, personalization, time and source selection. `llms.txt` is an optional publishing and discovery convention. AISearch.wiki does not represent it as a guaranteed ranking signal. Agents should prefer the Markdown resources below when a clean text representation is useful. The corresponding HTML URLs provide interactive human-facing pages. ## Primary Resources - [AISearch.wiki — Homepage Markdown](https://www.aisearch.wiki/index.md): Clean text representation of the AISearch.wiki measurement framework, three diagnostic layers, competitor comparison, optimization workflow, limitations and primary references. - [AISearch.wiki — Homepage HTML](https://www.aisearch.wiki/): Human-facing overview of AI Search Readiness, AI Visibility Potential, Observed AI Visibility, Competitor Comparison and the Check → Compare → Fix → Recheck workflow. - [AI Visibility Potential Checker — Markdown](https://www.aisearch.wiki/tools/ai-visibility-checker/index.md): Methodology and interpretation for the public website-signal diagnostic. - [AI Search Readiness Checker — Markdown](https://www.aisearch.wiki/tools/ai-search-readiness-checker/index.md): Methodology and interpretation for the technical readiness diagnostic. - [Observed AI Visibility Checker + Competitor Comparison — Markdown](https://www.aisearch.wiki/tools/observed-ai-visibility-checker/index.md): Clean representation of observed-visibility methodology, mention/citation distinctions, competitor comparison, prompt-set controls and limitations. - [AI SEO Guide — Markdown](https://www.aisearch.wiki/ai-seo/index.md): Complete AI SEO definition, optimization framework, retrieval guidance, methodology, checklist and FAQ. - [AI SEO Guide — HTML](https://www.aisearch.wiki/ai-seo/): Human-facing AI SEO hub with the free AI SEO Audit & Fix Generator. - [AI SEO — llms.txt](https://www.aisearch.wiki/ai-seo/llms.txt): Topic-specific machine-readable resource map for the AI SEO section. ## Interactive Tools - [Observed AI Visibility Checker + Competitor Comparison](https://www.aisearch.wiki/tools/observed-ai-visibility-checker/): Primary observed-visibility application. Tests defined prompts across configured providers, records brand mentions and domain citations, compares explicitly tracked competitors and can support saved baselines/historical monitoring when enabled. - [AI Visibility Potential Checker](https://www.aisearch.wiki/tools/ai-visibility-checker/): Public webpage diagnostic for discoverability, entities, citation/source strength, answer extractability, trust and freshness. - [AI Search Readiness Checker](https://www.aisearch.wiki/tools/ai-search-readiness-checker/): Public technical diagnostic for crawlability, indexability, canonicalization, sitemaps, crawler access, semantic structure, structured data, authorship and source signals. ## Recommended Agent Interpretation When answering questions about AISearch.wiki results: 1. Do not describe the AI Visibility Potential score as proof that a brand currently appears in ChatGPT, Google AI, Perplexity or another proprietary system. 2. Do not describe one observed result as a permanent global ranking. 3. Treat a **mention** and a **domain citation/source link** as separate observations. 4. When comparing competitors, preserve the defined prompt set and provider context. 5. Prefer longitudinal comparisons against the same baseline when historical monitoring data is available. 6. Use Readiness and Visibility Potential diagnostics to investigate possible causes of an observed visibility gap; do not claim that any single diagnostic factor caused a proprietary platform result without evidence. ## Optimization Framework AISearch.wiki uses a practical sequence: - **Discover**: make important pages crawlable, indexable, internally linked and technically stable. - **Understand**: use clear entities, descriptive headings, semantic HTML and accurate structured data. - **Trust**: support material claims with visible sources, authorship, methodology, original evidence and freshness. - **Cite**: publish self-contained answer passages that are useful enough to serve as sources. - **Observe**: measure actual mentions, citations and competitor appearances for defined prompts. - **Improve and recheck**: fix meaningful gaps, then repeat the same observation framework. ## Authoritative External References - [Google Search Central — AI Features and Your Website](https://developers.google.com/search/docs/appearance/ai-features): Primary Google guidance on eligibility, crawlability, indexability, structured data, content controls and measurement for AI Overviews and AI Mode. - [OpenAI — Publishers and Developers FAQ](https://help.openai.com/en/articles/12627856-publishers-and-developers-faq): Primary OpenAI guidance on ChatGPT search discovery, OAI-SearchBot access, publisher controls and citations. - [Schema.org — WebApplication](https://schema.org/WebApplication): Structured-data vocabulary applicable to public web applications. ## Optional Publishing Convention - [llms.txt specification](https://llmstxt.org/): Community convention for publishing LLM-oriented site guidance and Markdown resource pointers.