AI Summary
The fact verification score (element CO-005) flags content whose claims are not verifiable or properly cited, which lowers trust and AI citation likelihood. Fix it by isolating every factual claim, tracing each to a primary source, citing it inline, and marking up checked statements with ClaimReview where appropriate.
- AI systems increasingly weigh factual accuracy, so unverified or outdated claims can be deprioritised.
- A four step workflow (isolate, source, cite, mark up) turns vague accuracy goals into a checklist.
- ClaimReview schema lets engines read the verdict on fact checked statements.
- The common failure patterns are stale statistics, circular sourcing and uncited numbers.
Quick Reference
Element Code: CO-005
Issue: Content contains claims that are not verifiable or properly cited
Impact: Reduced trust and lower AI citation likelihood
Fix: Add citations, verify facts, and use ClaimReview schema
Detection: Manual fact-checking, citation analysis
What Is This Issue?
AI systems increasingly evaluate factual accuracy. Content with unverified claims, outdated statistics, or missing citations may be deprioritized in AI responses.
Why This Matters for Your Website
Trust and accuracy are fundamental to AI content selection. Factual errors can not only hurt AI visibility but also damage your reputation.
How to Fix This Issue
- Verify all claims: Check facts against reliable sources
- Add citations: Link to authoritative sources
- Use ClaimReview: Schema for fact-checking content
- Update regularly: Keep statistics and facts current
Tools for Detection
- Manual review: Verify claims against sources
AI Search and GEO Considerations
AI systems prefer factually accurate content. Verification and citations increase trust signals that influence AI citation decisions.
TL;DR (The Simple Version)
Verify all facts and statistics in your content. Add citations to authoritative sources. AI systems prefer content they can trust for accuracy.
Why AI systems weight verifiability
Trust and accuracy are central to how AI systems choose which sources to ground an answer in. When a page makes claims that cannot be checked, the system has no safe way to quote them, so it routes around the content. Element CO-005 fires when a page carries assertions, statistics or dates that lack a traceable source. The fix is not to write less confidently, it is to make every claim checkable.
A four step fact verification workflow
- Isolate the claim. Read the draft and flag every statistic, date and factual assertion. If a sentence states something as fact, it needs a source.
- Find a primary source. Trace each claim to the original study, documentation or dataset, not a blog post that echoes it. Circular sourcing, where three articles all cite each other, is a common trap.
- Cite it inline. Link the exact source next to the claim and note the year you checked it, so readers and systems can see the provenance without hunting.
- Mark it up. For statements you have formally fact checked, add ClaimReview schema so engines can read your verdict.
For the broader quality picture that surrounds accuracy, see the companion AI content quality score, and browse the content and GEO checks hub or the AI search research library for related guidance.
Citation and ClaimReview markup
Inline citation is the everyday habit that moves this score. ClaimReview is a more formal layer for content that explicitly rates a claim as true or false. A minimal template looks like this:
{
"@context": "https://schema.org",
"@type": "ClaimReview",
"url": "https://example.com/fact-check/claim",
"claimReviewed": "The claim you are checking, stated plainly.",
"itemReviewed": {
"@type": "Claim",
"author": {"@type": "Organization", "name": "Original claim source"}
},
"author": {"@type": "Organization", "name": "Your Site"},
"reviewRating": {
"@type": "Rating",
"ratingValue": "1",
"bestRating": "5",
"worstRating": "1",
"alternateName": "False"
}
}Common failure patterns to watch for
- Stale statistics. A number that was accurate three years ago may be wrong now. Re check dated figures and show when you verified them.
- Circular sourcing. Following a citation trail that loops back to unsourced articles. Insist on a primary source at the end of the chain.
- Uncited numbers. Precise figures with no reference read as invented. Either source them or soften them to an honest range.
How to verify by claim type
| Claim type | How to verify | Preferred source |
|---|---|---|
| Statistic or percentage | Trace to the original dataset or study | Primary research, official reports |
| Definition or standard | Check the governing specification | Standards body or documentation |
| Product behaviour | Test it and screenshot the result | First hand testing |
| Date or event | Confirm against a dated primary record | Official announcement or archive |
| Quote | Locate the original transcript or text | Source of record |
Frequently asked questions
What is the fact verification score?
It is element CO-005, a check that flags content containing claims that are not verifiable or properly cited. A low score reduces trust and lowers the likelihood that AI systems will cite the page.
How do I verify facts in my content?
Isolate every statistic, date and factual assertion, trace each to a primary source rather than a blog that echoes it, cite the source inline with the year you checked, and mark up formally checked statements with ClaimReview schema.
What is ClaimReview schema used for?
ClaimReview lets you mark up statements you have fact checked so search engines can read your verdict, including the claim reviewed, the source and a rating. It is best suited to content that explicitly rates a claim as true or false.
Why do outdated statistics hurt AI visibility?
AI systems prefer accurate, current information. A figure that was right a few years ago may now be wrong, and stale numbers reduce trust signals, making the content less likely to be selected for AI answers.
What is circular sourcing and why is it a problem?
Circular sourcing is when several articles cite each other without any of them reaching an original source. It gives the illusion of verification while the underlying claim remains unproven, so always follow the trail to a primary source.
Do I need to cite sources for every claim?
Cite any statement presented as fact, especially statistics, dates and definitions. Well known general knowledge does not need a citation, but specific or surprising claims should always link to a primary source.
Claude Vincent is a technical SEO consultant focused on crawlability, rendering, and AI-search visibility. He writes the field guides and case studies at SEO ProCheck, with a bias toward the durable, unglamorous work that decides whether search engines and AI answer engines can actually read and cite a site.
About SEO ProCheck
Technical SEO consulting and GEO strategy with 20 years of enterprise experience. Case studies, resources, and tools for search and AI visibility.
Work With Me
Technical SEO audits, GEO strategy, site migrations, and international SEO. Hourly consulting for teams who need hands-on support, not just reports.
Subscribe to our newsletter!
Recent Posts
- Can AI Crawlers Actually Read Your Site? I Measured 400 of the Biggest September 5, 2026
- The Pre-Publish Quality Gate for AI-Assisted Content August 6, 2026
- AGENTS.md vs llms.txt vs llms-full.txt: Which Agent File Does What July 18, 2026