What is an AI Readiness Score?

An AI Readiness Score is a measure from 0 to 100 that indicates how well your website can be read, understood, and recommended by AI agents like ChatGPT, Perplexity, Claude, and Google AI Overviews. It evaluates 48 specific checks across 5 categories: Access & Crawlability, Readability & Structure, Identity & Trust, Integration & Discovery, and Answerability & Content.

How does Score for AI work?

Score for AI fetches your website and analyzes it across 48 checks in 5 categories. We examine your robots.txt for AI bot access, check structured data and Schema.org markup, evaluate content depth and readability, verify meta tags and OpenGraph data, and test for AI-specific protocols like agent.json and MCP endpoints. Results are delivered in about 30 seconds.

Why should I care about AI readiness?

AI agents are rapidly becoming a primary way people find information. Google AI Overviews have reduced organic click-through rates by up to 61%. Gartner predicts traditional search volume will drop 25% by 2026. If AI agents cannot properly read and understand your website, you risk becoming invisible to a growing share of potential customers.

What AI agents does this cover?

Score for AI checks compatibility with all major AI agents including ChatGPT (GPTBot), Claude (ClaudeBot), Google AI Overviews (Google-Extended), Perplexity (PerplexityBot), Amazon (Amazonbot), Apple Intelligence (Applebot-Extended), Meta AI (meta-externalagent), Microsoft Copilot, and Common Crawl (CCBot).

How is the score calculated?

The score is calculated by running 48 individual checks across 5 weighted categories. Each check is pass/fail and contributes to its category score. The final score is a weighted average: Access & Crawlability, Readability & Structure, Identity & Trust, Integration & Discovery, and Answerability & Content. The maximum score is 100.

What's included in the free scan vs paid report?

The free scan gives you your overall AI readiness score plus a category-level breakdown showing where you stand in each of the 5 areas. The paid Full Report ($29) provides detailed check-by-check results, specific fix recommendations with code examples, priority ranking of issues, and competitive benchmarking against your industry.

How can I improve my AI readiness score?

Common improvements include: allowing AI bots in your robots.txt, adding Schema.org structured data, implementing proper meta tags and OpenGraph markup, creating a sitemap.xml, adding an RSS feed, writing substantial and well-structured content with proper heading hierarchy, and implementing AI-specific protocols like .well-known/agent.json.

How often should I scan my website?

We recommend scanning after any major website update, content change, or CMS migration. For active websites, a monthly scan helps ensure your AI readiness stays high as search engines and AI agents evolve their requirements. The AI landscape changes rapidly, so regular monitoring is important.

AI Readiness Checklist: 20 Things to Check Before 2026

🔓 Access & Crawlability

robots.txt allows AI bots — GPTBot, ClaudeBot, PerplexityBot, Google-Extended are not blocked. How to configure →
No CDN-level AI blocking — Cloudflare/Vercel “AI Scrapers” setting is not set to Block
Fast response time — Pages load in under 3 seconds for crawlers
No CAPTCHA barriers — AI bots aren't hitting CAPTCHA or challenge pages

📖 Readability & Structure

Semantic HTML — Using <article>, <section>, <nav>, <main>, <header>, <footer>
Proper heading hierarchy — Single H1, logical H2→H3 nesting, no skipped levels
Clean text-to-HTML ratio — At least 10% of page is visible text content
Sufficient content depth — Key pages have 500+ words of substantive content

🏢 Identity & Trust

Organization schema — JSON-LD with name, URL, logo, contact, sameAs. Implementation guide →
OpenGraph meta tags — og:title, og:description, og:image, og:type on every page
Article timestamps — article:published_time and article:modified_time on content pages
security.txt — /.well-known/security.txt with contact and preferred-languages

🔗 Integration & Discovery

Sitemap.xml — All important pages listed with accurate lastmod dates
RSS/Atom feed — Available and linked from HTML head
agent.json — /.well-known/agent.json describes your service. Guide →
llms.txt — /llms.txt provides LLM-friendly content summary. Guide →

📝 Answerability & Content

Factual specificity — Content includes specific numbers, dates, and verifiable claims
FAQ content — Conversational Q&A content with natural language questions
Internal linking — Contextual links between related pages and blog posts
Content freshness — Content updated within last 6 months with visible dates

Automate This Check

Rather than checking each item manually, scan your website with Score for AI. Our scanner covers all 20 of these items (and 28 more) automatically in 30 seconds. You'll get a score from 0-100 plus a category-by-category breakdown showing exactly where to focus.

For priority-ranked fixes with code examples, the Full Report ($29) provides a complete implementation roadmap.

AI Readiness Fundamentals and Implementation Guide

Understanding AI Readiness for Modern Websites

AI readiness encompasses comprehensive website optimization enabling artificial intelligence agents to effectively access, parse, understand, and recommend content across multiple platforms including ChatGPT, Claude, Perplexity, Google AI, and emerging AI search systems.

Technical Infrastructure Requirements for AI Compatibility

Server configuration optimization includes robots.txt AI bot permissions for GPTBot, ClaudeBot, Google-Extended, PerplexityBot, Amazonbot, Applebot-Extended, and CCBot crawlers enabling training data collection and search integration capabilities.

Content Structure and Semantic Markup Optimization

Semantic HTML implementation with proper heading hierarchy, article structuring, section organization, and list formatting facilitates machine comprehension and automated knowledge extraction for AI training and response generation systems.

Structured Data and Schema.org Implementation

JSON-LD structured data markup using Schema.org vocabularies provides machine-readable context including Organization, Person, Product, Service, Article, and specialized AI-specific schemas enabling enhanced understanding and factual extraction.

AI-Specific Protocols and Emerging Standards

Implementation of llms.txt documentation, agent.json metadata files, MCP endpoint configuration, and API documentation enables direct AI agent integration and automated content discovery across artificial intelligence platforms.

Continuous Monitoring and Performance Optimization

Regular analysis ensures sustained AI readiness performance as artificial intelligence technologies evolve, requirement standards change, and emerging protocols develop across major platforms and search engine integrations.