Key Takeaway
A complete AI page audit evaluates 7 dimensions: Indexability, Snippet & CTR, Intent & Value, Trust & E-E-A-T, Schema, AI Citeability, and Red Team Risk. Each dimension needs separate analysis and fixes.
What Is a Page-Level AI Audit?
A page-level AI audit is a systematic evaluation of a single web page across multiple dimensions to determine how likely AI systems are to find, understand, and cite that page. It is not a site audit — it evaluates one URL at a time, because AI systems cite pages, not domains.
This distinction matters. Your homepage might score 8.5 while your pricing page scores 3.2. A site-level audit would average these together and hide the problem. A page-level audit reveals exactly which pages need work and what to fix on each one.
The audit framework described in this guide evaluates every page across 7 branches: Indexability, Snippet & CTR, Intent & Value, Trust & E-E-A-T, Schema, AI Citeability, and Red Team Risk. Each branch measures a different aspect of how AI systems interact with your content — from basic access to advanced extractability.
Why Page-Level Matters
AI systems cite individual pages, not websites. When ChatGPT answers a question about SaaS pricing, it cites a specific pricing page — not the company’s domain. When Perplexity explains a concept, it links to the specific article that best answers the question — not the site’s homepage.
Your domain authority, overall site traffic, and aggregate backlink profile matter less than the quality of each individual page. A small blog with one excellent, well-structured article about JSON-LD schema can outperform a major tech publication’s surface-level coverage of the same topic.
Every commercial page, every pillar article, every pricing page, and every product page needs its own audit. The weakest pages are dragging down your AI visibility, and you can only find them by auditing page by page.
200
Total pages
8.1
Homepage score
4.2
Product pages avg
6.6
Misleading "site average"
The insight: A 6.6 site-level average hides the fact that the most commercially important pages (product pages at 4.2) are invisible to AI. Only page-level auditing reveals this.
The 7-Branch Audit Framework
The audit framework consists of 7 branches, each with a weighted score that rolls up into a single 0–10 overall score. Branches 1–6 are scored (weighted average = overall score). Branch 7 issues flags, not scores — a single flag can disqualify an otherwise high-scoring page.
1. Indexability
15%What it measures: Can AI crawlers access and parse your page? Checks robots.txt for GPTBot, ClaudeBot, Google-Extended, PerplexityBot.
Checks performed:
- robots.txt rules for AI crawlers
- Canonical tag configuration and consistency
- HTTP status code (200 OK required)
- JavaScript rendering requirements
- URL structure (clean, descriptive)
- XML sitemap inclusion
- Response time (timeout = uncrawlable)
- robots.txt blocking AI crawlers (most common)
- SPAs rendering all content client-side
- Canonical tag pointing to a different URL
- 301 redirect chains longer than 3 hops
- Soft 404s (200 status but error content)
Review robots.txt and ensure AI crawlers are allowed. Verify content appears in HTML source (View Source, not Inspect Element). Check canonical tags match the actual URL. Ensure sitemap includes all important pages.
Effort: XS to S (5–15 minutes for most fixes)
2. Snippet & CTR
15%What it measures: Does your page present itself well in AI and search contexts? Checks title tag, meta description, H1, OG tags, and favicon.
Checks performed:
- Title tag (50–60 chars, includes primary topic)
- Meta description (150–160 chars, compelling)
- H1 tag (exists, matches topic, one per page)
- Open Graph tags (og:title, og:description, og:image)
- Twitter Card tags
- Favicon presence
- Generic title tags ("Home | Company Name")
- Missing or duplicate meta descriptions
- Multiple H1 tags on a single page
- Missing Open Graph image
- Title tag and H1 semantic mismatch
Write a title tag with primary topic and brand. Write a meta description summarizing the page in one specific sentence. Ensure H1 matches the topic. Add og:title, og:description, and og:image tags.
Effort: XS to S (under 15 minutes per page)
3. Intent & Value
20%What it measures: Is the content genuinely useful for the query it should answer? Checks first 50 words, pricing visibility, comparison data, FAQ coverage, and content depth.
Checks performed:
- First 50 words define the topic clearly
- Product/service definition clarity
- Pricing visibility (shown or hidden?)
- Comparison data (tables, feature matrices)
- FAQ coverage with direct answers
- Content depth beyond surface level
- Content specificity (concrete examples vs vague claims)
- Opening paragraph is marketing copy, not a definition
- Pricing hidden behind "Contact sales"
- No comparison with alternatives or competitors
- FAQ section missing or vague
- Content is broad but shallow
Rewrite first 50 words as a clear definition. Make pricing visible. Add comparison tables. Include a FAQ section with direct, specific answers. Go deep on fewer topics rather than shallow on many.
Effort: M to L (30–90 minutes per page)
4. Trust & E-E-A-T
20%What it measures: Can AI verify your credibility? Checks author attribution, dates, about page, contact info, social proof, and source citations.
Checks performed:
- Author attribution (name, role, bio link)
- Publication date visible on page
- Last updated date visible
- About page exists and is linked
- Contact information accessible
- Privacy policy linked
- Source citations for claims and statistics
- Consistent entity information across site
- No author name on content pages
- No publication or update dates
- About page is a one-paragraph stub
- Testimonials use only first names ("Sarah M.")
- Statistical claims without source attribution
Add named author with credentials and linked bio. Display publication and update dates. Expand About page. Use full names and verifiable details in testimonials. Cite sources for all statistics.
Effort: S to M (15–60 minutes per page)
5. Schema
10%What it measures: Is your page machine-readable through structured data? Checks JSON-LD presence, Article/Product/FAQPage/Organization/BreadcrumbList/Person schema.
Checks performed:
- JSON-LD presence (preferred format)
- Article schema (for content pages)
- Organization schema (site level)
- Product schema (product/pricing pages)
- FAQPage schema (for FAQ sections)
- BreadcrumbList schema
- Person schema (author bios)
- Schema validation (no errors or warnings)
- No structured data at all (surprisingly common)
- Schema present but contains errors
- FAQ sections exist in HTML but lack FAQPage schema
- Article schema without datePublished or dateModified
- Organization schema with incorrect data
Add JSON-LD for Article or Product schema as appropriate. Add FAQPage schema for any FAQ section. Add Organization schema at site level. Validate with Google Rich Results Test.
Effort: S to M (15–60 minutes)
6. AI Citeability
20%What it measures: Will AI systems actually quote your content? Checks quotable sentences, self-contained paragraphs, statistics with sources, entity clarity, and extractability.
Checks performed:
- Quotable sentences (specific, self-contained facts)
- Self-contained paragraphs (make sense in isolation)
- Statistics with source attribution
- Entity clarity (names, not pronouns)
- Definition density (clear definitions present?)
- List and table presence (extractable formats)
- Content extractability (passages stand alone?)
- Pronoun-heavy writing ("It does this, then it does that")
- Paragraphs that depend on previous context
- Statistics without sources ("Studies show 80%...")
- Marketing superlatives without evidence
- Long paragraphs with mixed topics
Replace pronouns with entity names. Make each paragraph self-contained. Add source links for all statistics. Replace superlatives with specific metrics. Break long paragraphs into focused, extractable units.
Effort: M to L (15–90 minutes per page)
7. Red Team Risk
FlagsWhat it measures: What could go wrong if AI cites this page? Flags YMYL content without attribution, unverifiable claims, hallucination triggers, and exaggerated statistics.
Checks performed:
- YMYL content without appropriate attribution
- Unverifiable claims ("guaranteed results")
- Potential hallucination triggers (ambiguous statements)
- Controversial claims without balanced attribution
- Medical/legal/financial advice without credentials
- Exaggerated statistics or results
- Content contradicting widely accepted facts
- "Our product will increase your revenue by 500%"
- Health claims without medical citations
- "The only tool you'll ever need"
- Financial projections presented as certainties
- Customer results without context or methodology
Remove or properly attribute risky claims. Replace superlatives with specific, verifiable statements. Add professional credentials for YMYL content. Present projections as ranges, not guarantees.
Effort: S (5–15 minutes to review and fix)
Severity Classification
Every issue found during an audit is classified by severity. This determines fix priority.
Blocker
Page cannot be cited at all
Example: robots.txt blocks AI crawlers
Typical: 0–1 per page
High
Significantly reduces AI visibility
Example: No author attribution on YMYL content
Typical: 1–4 per page
Medium
Missed optimization opportunity
Example: Missing FAQ schema markup
Typical: 3–6 per page
Low
Minor improvement possible
Example: Meta description could be more specific
Typical: 2–5 per page
Triage strategy: Fix Blockers immediately — they prevent all AI visibility. Then fix High issues for the biggest improvement per effort. Medium and Low can be batched over time. Most pages have 8–15 total issues. A well-optimized page typically has 0 Blockers, 0–1 High, 2–3 Medium, and 1–3 Low.
Effort Estimation Framework
Every fix recommendation includes an effort estimate so you can plan your optimization work realistically.
Under 5 minutes
Updating a meta description, adding a publication date, fixing a canonical tag
5–15 minutes
Writing an author bio, adding FAQ schema markup, rewriting the first 50 words
15–60 minutes
Implementing full JSON-LD schema, rewriting a page for extractability, adding comparison tables
Over 1 hour
Major content restructuring, adding pricing transparency, creating author bio pages with credentials
Efficiency tip: Start with all XS fixes across your most important pages. You can fix 10 XS issues in under an hour and see measurable score improvements. Then work through S issues. By the time you reach M and L, you’ll have already improved your overall visibility significantly.
Score Interpretation
The overall score is a weighted average of all 7 branch scores (except Red Team, which is qualitative). Here’s how to interpret it.
8–10
AI-Ready (Pass)
Well-positioned for AI citations. Focus on maintaining quality and freshness. Monitor for regression when you make changes.
5–7.9
Needs Work
Specific areas need improvement. Look at branch-level scores to identify weakest dimensions. A 7.5 overall with a 3.0 on Trust has a clear, focused problem to solve.
0–4.9
Critical Issues
Fundamental problems blocking AI visibility. Usually an access issue (robots.txt), a trust issue (no attribution), or a content issue (marketing fluff). Fix Blockers first.
Branch-level diagnosis
The most useful insight isn’t the overall score — it’s the gap between your strongest and weakest branches. A page with all branches at 6.0 is in a different situation than a page with five branches at 8.0 and two at 2.0. The second page needs targeted fixes on two dimensions. The first page needs broad improvement.
Sample Audit Walkthrough
A real-world walkthrough showing how the framework works in practice.
Page: A SaaS company’s pricing page (anonymized)
Overall Score: 5.8 / 10 — Needs Work
Branch scores
Issues found (12 total)
| # | Issue | Severity | Fix | Effort |
|---|---|---|---|---|
| 1 | First 50 words contain no product definition | High | Open with "[Product] is [what] for [who] at [price]" | XS |
| 2 | No author attribution anywhere on page | High | Add author name, role, and linked bio | S |
| 3 | No publication or update date | High | Add visible dates + Article schema dateModified | XS |
| 4 | Testimonials use only first names | Medium | Add full names, roles, and company names | S |
| 5 | Missing Product schema with pricing data | Medium | Add JSON-LD Product schema with price, currency | S |
| 6 | Missing FAQ schema for existing FAQ section | Medium | Add FAQPage schema markup for 6 existing Q&As | S |
| 7 | Meta description is generic | Medium | Rewrite to include product name, price point, key benefit | XS |
| 8 | Paragraphs use "it" instead of product name | Medium | Replace pronouns with entity name throughout | M |
| 9 | Title tag doesn't include pricing | Low | Change to "[Product] Pricing — Plans from $X/mo" | XS |
| 10 | No comparison table with alternatives | Low | Add feature comparison table vs top 2 competitors | M |
| 11 | Social proof logos without context | Low | "Trusted by X customers" or specific metrics | XS |
| 12 | H2 headings are vague ("Our Plans") | Low | Rewrite to specific ("Pricing Plans: Free and Pro") | XS |
DIY Audit Checklist
Use this checklist to audit any page manually. Check each item and note whether it passes or fails.
Indexability
- robots.txt allows AI crawlers (GPTBot, ClaudeBot, PerplexityBot)
- Page returns HTTP 200
- Canonical tag matches the actual URL
- Content appears in HTML source (not JavaScript-only)
- Page is included in XML sitemap
Snippet & CTR
- Title tag exists, 50–60 characters, includes primary topic
- Meta description exists, 150–160 characters, specific
- Exactly one H1 tag, matches page topic
- Open Graph tags present (og:title, og:description, og:image)
- Favicon present
Intent & Value
- First 50 words contain a clear definition of the page topic
- Pricing is visible (if applicable)
- Comparison data present (tables, matrices)
- FAQ section answers common questions directly
- Content goes beyond surface level
Trust & E-E-A-T
- Named author with credentials displayed
- Publication date visible
- Last updated date visible
- About page exists and is linked
- Contact information accessible
- Source citations for claims and statistics
Schema
- JSON-LD present (check with Google Rich Results Test)
- Article or Product schema (as appropriate)
- FAQPage schema (if FAQ section exists)
- Organization schema (at site level)
- BreadcrumbList schema
AI Citeability
- Paragraphs are self-contained (make sense in isolation)
- Entity names used instead of pronouns
- Statistics include source attribution
- Content can be extracted without losing meaning
- Clear definitions present
Red Team
- No unverifiable superlative claims
- No medical/legal/financial advice without credentials
- No potentially misleading statistics
- No content that contradicts established facts
Skip the manual work: Automated audit (60 seconds)
TurboAudit runs all 7 branches automatically, checking 120+ individual signals per page. You get a scored report with prioritized fixes, severity classifications, and effort estimates — in about 60 seconds per URL.
Audit your page free →Frequently Asked Questions
A page-level AI audit evaluates a single web page across 7 dimensions — Indexability, Snippet & CTR, Intent & Value, Trust & E-E-A-T, Schema, AI Citeability, and Red Team Risk — to determine how likely AI systems are to find, understand, and cite that page. Unlike site audits, it evaluates one URL at a time because AI systems cite pages, not domains.
AI systems cite individual pages, not websites. Your homepage might score 8.5 while your pricing page scores 3.2. A site-level audit would average these together and hide the problem. Page-level auditing reveals exactly which pages need work and what to fix on each one.
An automated audit with TurboAudit takes approximately 60 seconds per URL. A manual audit using the DIY checklist in this guide takes 15-30 minutes per page, depending on how thoroughly you check each dimension.
An overall score of 8.0 or above indicates a page is AI-ready. Scores between 5.0-7.9 mean specific dimensions need improvement. Below 5.0 indicates critical issues. Focus on improving the lowest-scoring branch first for the biggest impact.
The three most common issues across all page types are: (1) missing author attribution, (2) first 50 words that don't define the page topic, and (3) missing or incomplete schema markup. All three are fixable in under 30 minutes per page.
Re-audit after making changes to verify improvements. For ongoing monitoring, re-audit key pages at least every 13 weeks (quarterly). Any time you make significant content changes, a re-audit ensures you haven't introduced new issues.
Yes. You can audit any publicly accessible URL. Competitor audits are valuable for understanding where they're strong and where you can differentiate. If a competitor's pricing page scores 4.0 and you can push yours to 8.0, you have a significant advantage in AI citations.
A Blocker issue means the page cannot be cited at all — typically a robots.txt block or a page that returns a non-200 status code. A High severity issue significantly reduces AI visibility but doesn't completely prevent citation — for example, missing author attribution on YMYL content.
Deep-dive guides in this series
Audit Your AI Search Visibility
See exactly how AI systems view your content and what to fix. Join the waitlist to get early access.
Audit Your AI Search Visibility
See exactly how AI systems view your content and what to fix. Join the waitlist to get early access.
Related Articles
Continue exploring this topic with these in-depth guides.
Schema Markup for AI Search: Complete Guide
JSON-LD, FAQ, Product, Organization — which schema types matter for AI and how to implement them correctly.
Read article2The First 50 Words Rule: Why Your Opening Matters
AI systems disproportionately weigh your opening paragraph. Learn the formula for a citation-worthy intro.
Read article3How to Write AI-Quotable Content
Self-contained paragraphs, statistics with sources, entity clarity — the mechanics of extractable writing.
Read article4Content Depth vs Content Length: What AI Actually Wants
More words ≠ more citations. AI rewards depth, specificity, and structure — not word count.
Read article5JavaScript and AI: Why Hidden Content Kills Visibility
Client-rendered content is invisible to most AI crawlers. Understand the rendering gap and how to fix it.
Read article6llms.txt: Should You Implement It?
The emerging llms.txt standard — what it is, who supports it, and whether it's worth adding to your site.
Read article7Indexability & AI Crawl Access: Complete Guide
Robots.txt, canonical tags, noindex, redirect chains, HTTPS — every technical signal that determines whether AI systems can access and process your page.
Read article8Snippet & CTR Optimization for AI Search
Title tags, meta descriptions, Open Graph, breadcrumbs, and date signals — how to optimize every metadata element AI systems read before analyzing your page.
Read article9Content Intent & Value: What AI Evaluates Beyond Keywords
How AI systems evaluate whether your content matches user intent, delivers genuine value, and avoids thin or misleading content signals.
Read article10Schema Markup for AI Citation: Implementation Guide
JSON-LD schema types that maximize AI citation rates — Article, FAQPage, HowTo, Product, BreadcrumbList — with implementation examples and validation tools.
Read article11SEO Risk Audit: Google Spam, FTC Compliance, and AI Blacklisting
The disqualifying risk flags that can result in Google manual actions, legal liability, or AI system blacklisting — regardless of your content quality score.
Read article12AI Crawlers & robots.txt: Complete Reference Guide
All 14 AI crawlers, their roles (training vs. citation), and how to configure robots.txt to control AI crawler access without blocking citations.
Read article