--- title: "AI-Readiness Audit: llms.txt, SSR Parity, Bot Allowlists, Citation Spot-Checks" description: "Most audits are 5 years behind on AI. We audit schema coverage, server-side rendering parity, llms.txt, AI crawler allowlists (GPTBot, ClaudeBot, PerplexityBot, Google-Extended) and your brand's citation presence across Perplexity, ChatGPT, Claude, and Gemini." source: "https://www.kensink.com/website-audit/ai-readiness/" canonical: "https://www.kensink.com/website-audit/ai-readiness/" --- ★ AI-readiness Audit slots open GPTBot · ClaudeBot · PerplexityBot · Google-Extended AI-READINESS · 06 LAYERS # Most audits are five years behind on AI. AI crawlers behave differently than Google did in 2012. If your audit checks schema.org but skips `llms.txt`, SSR parity, bot allow-lists, and citation spot-checks across answer engines, you have a 2019 audit. Here’s the 2026 layer we add to every engagement. [Book AI-readiness audit →](https://www.kensink.com/contact?intent=audit-ai) [← Back to overview](https://www.kensink.com/website-audit) \[THE 2026 LAYER · 06 CHECKS\] ## Six layers we add on top of the technical audit. Each layer is independently auditable, and each one fixes a different way AI search will quietly route around your site. LAYER-01 / 06 01 / 06 ### Server-side rendering parity If your content only exists after JavaScript runs, AI crawlers see nothing. Most of them don’t execute JS reliably. SSR or SSG is now table stakes. - HTML fully rendered server-side or statically generated - Content exists in raw HTML without JS execution - Spot-check priority templates via ‘view source’, not rendered DOM - If using React/Vue: SSR (Next.js, Nuxt), SSG, or selective hydration - GSC URL Inspection ‘rendered HTML’ matches the served HTML for content LAYER-02 / 06 02 / 06 ### llms.txt published at root Plain-text index of high-value URLs for LLM agents. A modern analogue to sitemap.xml: an emerging convention, low cost, with real upside. - llms.txt published at /llms.txt - Includes high-value URLs (services, pillars, about, contact) - Hierarchical structure with headings if the site is large - Linked from robots.txt where appropriate - Kept in sync with the canonical sitemap LAYER-03 / 06 03 / 06 ### AI crawler allowlists If your WAF or robots.txt silently blocks AI bots, your brand will never surface in answer engines, and you won’t see the failure in any tool. - robots.txt explicitly allows GPTBot - robots.txt explicitly allows ClaudeBot (Anthropic) - robots.txt explicitly allows PerplexityBot - robots.txt explicitly allows Google-Extended (Gemini training) - robots.txt explicitly allows CCBot (Common Crawl) - WAF / bot-management rules don’t shadowban the above - Strategic block? Only if you have a documented reason and you understand the discoverability cost LAYER-04 / 06 04 / 06 ### Structured data, validated Schema isn’t just a plugin output. It’s how AI systems parse you into facts they can cite. Validate it, and make sure the fields agree with what’s on the page. - Structured data validates cleanly in Google Rich Results Test - Structured data validates cleanly in Schema.org validator - Entity consistency: org name, founding date, founders, product names appear identically across schema and visible copy - Schema generated from the same source of truth as the rendered content - Validation step wired into CI so regressions don’t ship LAYER-05 / 06 05 / 06 ### Answer-ready content shape LLMs favor short, definitional paragraphs near the top of the page and H2s phrased as questions. Long preamble buries you in the citation race. - Definitions appear near the top of the page, not buried under context - Short, declarative paragraphs (2–4 sentences) - Clear H2 questions for the queries you want to be cited on - Tables and lists for comparison-style queries - Author bylines + credentials for E-E-A-T LAYER-06 / 06 06 / 06 ### Citation spot-check (monthly) The only test that matters: are you cited when buyers ask the questions your service answers? Run it manually, monthly, across the four major answer engines. - 5–10 brand-relevant queries spot-checked in Perplexity - Same queries spot-checked in ChatGPT (with browsing) - Same queries spot-checked in Claude (with web tool) - Same queries spot-checked in Gemini - Citations tracked over time: are you gaining or losing surface? - Where competitors are cited and you aren’t, the gap becomes a content target \[SCHEMA COVERAGE · BASELINE\] ## The minimum schema every site type should ship. If a page type below has nothing in the right column, you have an AI-readiness gap. Every type below should be validated in the Google Rich Results Test before deploy. Page type Required schema Homepage Organization, WebSite (with SearchAction) Article / blog post Article or BlogPosting, Author (Person), BreadcrumbList Product Product, Offer, AggregateRating, Review Service Service, Organization FAQ FAQPage (use only for real FAQs) Case study Article · optional Review / Organization context Event Event Video VideoObject Contact ContactPage, PostalAddress 2–3 DAY ENGAGEMENT ## See where your brand surfaces in AI answers, and where it doesn’t. Two to three days, six layers audited, with the citation spot-check report your sales team will actually share in the kickoff deck. [Book AI-readiness audit →](https://www.kensink.com/contact?intent=audit-ai) [See full framework](https://www.kensink.com/website-audit/framework)