AEO Technical Audit: Complete Website Assessment Checklist

Before optimizing content for AI search, technical foundations must be solid. AI systems can't cite content they can't access, parse, or understand. A comprehensive technical audit identifies barriers preventing AI visibility and prioritizes fixes by impact.

This checklist covers every technical factor affecting how AI crawlers discover, process, and evaluate your website.

Section 1: AI Crawler Access Audit

AI systems use dedicated crawlers with specific behaviors. Standard SEO crawler audits miss AI-specific issues.

Robots.txt Analysis

Check for each AI crawler:

Audit steps:

1. Access robots.txt directly at domain.com/robots.txt
2. Search for each AI user-agent
3. Verify Allow/Disallow directives
4. Check for wildcards affecting AI crawlers
5. Test with robots.txt testing tools

Common issues found:

• Blanket "Disallow: /" blocking all bots
• Legacy rules inherited from outdated templates
• Conflicting directives (both Allow and Disallow for same paths)
• Missing AI crawlers entirely (neither allowed nor blocked)

Server Response Testing

AI crawlers may receive different responses than browsers.

Test methodology:

curl -A "GPTBot" -I https://yourdomain.com/target-page
curl -A "ClaudeBot" -I https://yourdomain.com/target-page
curl -A "PerplexityBot" -I https://yourdomain.com/target-page

Response codes to check:

Security system audit:

• Web application firewall (WAF) rules
• CDN bot detection settings
• Rate limiting thresholds
• Geographic restrictions
• User-agent filtering

Crawl Budget Analysis

Evaluate how efficiently AI crawlers can access your content.

Factors to assess:

Section 2: Structured Data Audit

Schema markup provides machine-readable context AI systems use for extraction and citation.

Schema Implementation Check

Audit each page type:

Schema Validation Process

Testing sequence:

1. Syntax validation - JSON-LD parses without errors
2. Schema.org compliance - Types and properties match specification
3. Google Rich Results - Eligible for enhancements
4. Field completeness - Required and recommended fields populated

Common schema errors:

Schema Quality Assessment

Beyond syntax, evaluate semantic quality.

Quality factors:

• Accuracy: Schema content matches visible page content
• Completeness: All applicable fields populated
• Specificity: Most specific @type used (not generic Thing)
• Freshness: dateModified reflects actual updates
• Authority: Author and publisher properly attributed

Section 3: Content Accessibility Audit

AI systems must access and parse your content directly.

JavaScript Rendering Analysis

Content hidden behind JavaScript may be invisible to AI crawlers.

Testing process:

1. Disable JavaScript in browser
2. View page source (not rendered DOM)
3. Check if primary content appears
4. Verify schema markup in source

JavaScript dependency matrix:

Content Parsing Test

Verify AI systems can extract meaningful content.

Manual extraction test:

1. Copy page source HTML
2. Strip all markup programmatically
3. Assess remaining text coherence
4. Identify content locked in images or PDFs

Accessibility factors:

Factor	Good Practice	Issues to Fix
Text in HTML	Direct text content	Text in images
Heading structure	Logical H1→H6 flow	Skipped levels, multiple H1s
List formatting	Semantic /	Visual-only formatting
Table structure	Proper markup Tables for layout Section 4: Site Architecture Audit Information architecture affects how AI systems understand content relationships. URL Structure Analysis URL quality checklist: Factor Optimal Suboptimal Fix Priority Hierarchy /category/subcategory/page /p?id=12345 High Keywords /blog/aeo-optimization /blog/post-123 Medium Depth 3-4 levels max 6+ levels Medium Parameters Minimal Multiple tracking params Low Internal Linking Assessment Internal links help AI systems discover and contextualize content. Audit metrics: Metric Target Action If Below Links to priority pages 10+ internal links Add contextual links Orphan pages 0 Connect to relevant content Link anchor text Descriptive Update generic anchors Broken internal links 0 Fix or remove Navigation and Hierarchy Structure assessment: Primary navigation includes key AEO target pages Breadcrumbs present and schema-marked Category pages properly structured Related content links present on each page Section 5: Performance Audit Site speed affects both crawlability and user experience signals. Core Web Vitals for AI Benchmark assessment: Metric Good Needs Work Poor LCP (Largest Contentful Paint) <2.5s 2.5-4s >4s FID (First Input Delay) <100ms 100-300ms >300ms CLS (Cumulative Layout Shift) <0.1 0.1-0.25 >0.25 TTFB (Time to First Byte) <200ms 200-500ms >500ms Server Performance Infrastructure checks: Component Check Impact on AI Server location Geographic distribution Crawl speed CDN configuration Edge caching Availability Compression Gzip/Brotli enabled Efficiency HTTP/2 or HTTP/3 Protocol support Connection handling Section 6: Security and Trust Signals Technical security indicators contribute to authority assessment. Security Audit Checklist Factor Required Status HTTPS everywhere Yes Check Valid SSL certificate Yes Check HSTS enabled Recommended Check Mixed content issues None Check Security headers Present Check Audit Prioritization Framework Not all issues require immediate attention. Prioritize by impact. Critical (Fix Immediately) AI crawlers blocked entirely HTTPS not implemented Primary content requires JavaScript Schema has syntax errors High Priority (Fix Within 2 Weeks) Slow server response to crawlers Missing schema on key page types Poor internal linking to priority content WAF blocking legitimate AI access Medium Priority (Fix Within 1 Month) Incomplete schema fields URL structure improvements Core Web Vitals optimization Navigation enhancements Lower Priority (Ongoing Improvement) Minor schema enhancements Additional internal linking Secondary page optimization Post-Audit Action Plan Convert audit findings into implementation roadmap. Documentation template: Issue: [Specific finding] Impact: [Critical/High/Medium/Low] Current State: [What's happening now] Target State: [Desired outcome] Implementation: [Specific steps] Verification: [How to confirm fix] Key Takeaways Conduct thorough AEO technical audits: Test AI crawler access specifically - Robots.txt and server responses to AI user-agents Validate structured data comprehensively - Syntax, compliance, and semantic quality Verify content accessibility - JavaScript rendering, HTML parsing, content extraction Assess site architecture - URL structure, internal linking, navigation hierarchy Measure performance factors - Core Web Vitals, server response, infrastructure Prioritize by impact - Critical issues first, then systematic improvement Technical audits reveal hidden barriers to AI visibility. Regular assessment ensures your site remains accessible as AI systems and your content evolve. Related Articles: Technical AEO Optimization: Schema, Structured Data, and Code Implementation AEO Schema Markup: Priority Types and Implementation AEO Optimization Checklist: 50-Point Implementation Guide AEO Implementation: 6-Month Roadmap and Timeline Matt Pru Get started with Stackmatix! Get Started Share On: Join thousands of venture-backed founders and marketers getting actionable growth insights from Stackmatix. Thank you! Your submission has been received! Oops! Something went wrong while submitting the form. By submitting this form, you agree to our Privacy Policy and Terms & Conditions. Related Blogs YouTube SEO for AI Search: How to Get Cited in AI OverviewsRead Article YouTube Advertising Reddit: What Redditors SayRead Article You.com AI Search: Privacy-First Search Engine Review (2026)Read Article Trusted by 100's of venture-backed startups and scaleups around the world. Let's Go Let’s create something amazing together. Careers BlogContact Us (415) 993-9077 AI AdsAI SEOChatGPT AdsReddit Ads © Stackmatix  All Rights Reserved, 2025 Terms of ServicePrivacy Policy