Why AI-ready is separate from SEO
Google still cares about titles, sitemaps, and Core Web Vitals. ChatGPT search, Claude, Perplexity, and coding agents add a different question: can a machine read your public content cleanly on the first fetch?
AuditHQ reports an AI-ready score alongside performance and SEO. It is not a ranking guarantee — it is a readiness checklist for citation, summarization, and agent tooling.
If your homepage is a JavaScript shell with almost no text in the raw HTML, search bots may eventually render it — but many agents will not wait. That gap shows up here before it shows up in your analytics.
What the AI-ready score checks
llms.txt — a Markdown index at /llms.txt pointing agents to your most important pages (llmstxt.org convention). We check that it exists, uses a proper H1, and looks like Markdown rather than an error page.
Optional llms-full.txt — a single-file dump for one-shot ingestion when you want agents to read everything without following links.
AI search bots in robots.txt — blocking OAI-SearchBot, Claude-SearchBot, PerplexityBot, and similar UAs removes you from those answer engines. Training bots (GPTBot, ClaudeBot, Google-Extended) are noted as policy choices, not automatic fails.
Markdown mirrors — clean .md copies of key pages so agents skip nav chrome and cookie banners.
Server-rendered extractability — raw HTML word count vs what a real browser renders. Large gaps mean agents see an empty page.
Answer-friendly structure — lists and tables, reasonable paragraph length, question-style headings, and a direct answer near the top of the first section.
How it fits next to performance and SEO
Performance and Core Web Vitals still answer whether humans can use the site fast. Technical SEO still answers whether crawlers can find and trust the canonical URL.
AI-ready answers whether the content that matters is actually present in what agents fetch — and whether you have invited the right bots in robots.txt.
Structured data (JSON-LD for Organization, SoftwareApplication, FAQ, Breadcrumbs) stays in the SEO score. It helps rich results in search; AI-ready focuses on plain-text reachability and agent files.
A practical fix order
1. Unblock AI search bots if you want citations — unless you deliberately opted out.
2. Publish llms.txt with links to docs, pricing, and your strongest explainer pages.
3. Fix SSR gaps on money pages — hero copy and pricing should appear in view-source, not only after hydration.
4. Add scannable structure: short paragraphs, bullets for features, tables for plans, H2/H3 questions where they match real queries.
5. Re-run on schedule — agent policies and your deploy cadence both move faster than quarterly SEO reviews.
How AuditHQ surfaces it
Every website audit includes an AI-ready panel on the report: pass/suggest/fail checks, a 0–100 score, and a Strong / Partial / Needs work grade.
It sits beside live page checks (HTTPS, titles, JSON-LD), the load waterfall, competitor scores, and — on Pro — screenshot diff against the previous run.
Run a fresh audit after changing llms.txt or robots.txt. Cached probes from an older run will not reflect today's bot policy.