How to Fix Every Agent Readiness Finding
The Agent Readiness Audit tests whether AI crawlers — GPTBot, ClaudeBot, PerplexityBot, GoogleOther, Bytespider — can access, parse and accurately extract your content. Traditional SEO ranks you in Google; agent readiness gets your content into ChatGPT, Claude, Perplexity, Gemini and the answer engines users increasingly query before they ever see a SERP. This index covers every fix.
By finding category
The audit raises issues across these areas. Pick yours below:
🤖 Fix AI crawler robots.txt blocks LIVE
If your robots.txt disallows GPTBot, ClaudeBot or PerplexityBot, AI answer engines cannot index your content — even if Google can. The trade-off between AI training opt-out and AI-search visibility, and how to allow the search bots while blocking the training bots.
📄 Add an llms.txt file LIVE
The emerging /llms.txt standard tells LLMs which content matters and how to consume it. Where to put it, what to include, common patterns for documentation sites, e-commerce, blogs and SaaS marketing sites.
🏛️ Fix missing or incomplete JSON-LD LIVE
LLMs lean heavily on structured data when extracting facts. Article, Product, Organization, Person, FAQPage, HowTo schemas — which to add per page type, the @graph pattern for combining multiple types, and how to validate.
📐 Fix non-semantic HTML structure LIVE
LLMs parse <article>, <section>, <nav>, <main>, <header>, <footer> as structural cues. Wall-of-div pages confuse extraction. How to refactor div-soup templates to semantic HTML5 without breaking visual design.
📖 Fix poor content extractability LIVE
Content hidden behind JavaScript-only rendering. Critical facts buried in images. Tables rendered as <div> grids. The reader-mode test: if Firefox Reader Mode shows nothing, LLMs see nothing.
⚡ Fix slow rendering for AI crawlers LIVE
Most AI crawlers do not execute JavaScript, or execute it with tight timeouts. Server-side rendering, static generation or pre-rendering for the bot user agents. The pre-rendering services that work and the ones that fail silently.
👤 Fix missing author and trust signals LIVE
LLMs cite sources they trust. Visible authorship, organisation pages, about pages, contact info, citations, expert credentials. The E-E-A-T patterns that AI engines specifically reward when picking content to cite.
🔗 Fix canonical and URL conflicts LIVE
AI crawlers see the same content at different URLs and pick whichever they hit first. Consistent canonicals, consolidated URL parameters, redirect tidiness — same fundamentals as Google SEO but with less forgiveness.
By platform
How agent-readiness fixes apply depends on where your content lives:
📰 Fix agent readiness in WordPress PLANNED
Schema plugins that work for LLMs vs ones that only handle Google, robots.txt management, the llms.txt plugin landscape, and pre-rendering JavaScript-heavy themes.
🛒 Fix agent readiness in Shopify PLANNED
Product schema fully populated, FAQ schema on product pages, the platform-level robots.txt limitations, and getting your products into AI shopping answers.
⚛️ Fix agent readiness in React / Next.js PLANNED
SSR vs SSG vs ISR for AI crawlers, structured data in Next.js Metadata API, the hydration vs first-paint trade-off, and pre-rendering edge cases.
What our Agent Readiness Audit checks
The audit emulates AI crawler requests with the actual user agents (GPTBot, ClaudeBot, PerplexityBot, etc.), checks robots.txt and llms.txt, evaluates JSON-LD coverage, scores semantic HTML structure, tests JavaScript-rendering dependence and measures content extractability. For the complete reference, see the Agent Readiness Guide or view a sample report.
🛰️ Audit your readiness first
Free audit. See exactly which AI crawlers can reach you, which structured data is missing, and which content is invisible to LLMs.
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