AI Citation Likelihood Scorer
This tool analyzes your page content and scores how likely AI engines (ChatGPT, Claude, Perplexity, Google AI Overviews) are to cite it as a source. Paste your page content or URL, and the tool checks for the structural signals that AI retrieval systems look for when selecting sources. Everything runs in your browser. Your content never leaves your device.
100% client-side. Answers stay in your browser (ons-ai-citation-inputs).
AI citation score
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Answer signals to score
0 of 10 signals answered (10 not counted as zero)
Content signals
Factual accuracy
Does your content cite primary sources (studies, official data)?
Structured answers
Does content use a direct answer format (question, then answer in the first sentence)?
Schema markup
Does the page have FAQ, Article, or HowTo schema?
Content depth
Word count of primary content
Author credentials
Does the author have demonstrable expertise (bio, credentials, byline)?
Brand mentions
Is the brand or site mentioned by other trusted sources?
Content freshness
How recently was content updated?
Direct answer format
Does the content answer the exact query in the first 100 words?
List and table structure
Does content use numbered lists, tables, or step-by-step format?
HTTPS and Core Web Vitals
Is the site on HTTPS with Good Core Web Vitals scores?
Score contribution
Answer at least one signal with points to see the breakdown chart.
Full signal breakdown
| Signal | Your score | Max | Weight | % contribution |
|---|---|---|---|---|
| Factual accuracy | Not answered | 2 | 15% | — |
| Structured answers | Not answered | 2 | 15% | — |
| Schema markup | Not answered | 2 | 10% | — |
| Content depth | Not answered | 2 | 10% | — |
| Author credentials | Not answered | 2 | 10% | — |
| Brand mentions | Not answered | 2 | 10% | — |
| Content freshness | Not answered | 2 | 10% | — |
| Direct answer format | Not answered | 2 | 10% | — |
| List and table structure | Not answered | 2 | 5% | — |
| HTTPS and Core Web Vitals | Not answered | 2 | 5% | — |
How this tool works
The AI citation scorer evaluates how likely a page or content block is to be cited by large language models in generative AI responses, a quality sometimes called GEO (Generative Engine Optimization) or AEO (Answer Engine Optimization). The tool analyzes five factors that correlate with LLM citation behavior in published research: presence of first-party statistics or original data, explicit attribution to a named author or organization, structured formatting (headers, numbered steps, comparison tables), factual claim density, and topical depth relative to a single focused subject. Each factor is scored 0-20 and summed to a 0-100 citation readiness score. The tool also flags patterns that reduce citation likelihood: hedging language, unsupported superlatives, thin paragraph density, and absence of a clear primary source claim. Key assumption: scoring weights are based on published retrieval-augmented generation research and content signal analysis, not direct access to any LLM's training data or ranking internals. Different models prioritize different signals. Edge case: LLMs update citation behavior when models are retrained on newer data. A page that scores 85 today may see different citation frequency after a model update. This score measures observable content quality signals, not a guaranteed citation rate.
Worked example
You paste a blog post about mortgage rates. The tool checks: - Direct answer in first 60 words: Yes (20 points) - FAQPage JSON-LD: Yes (15 points) - Cites Federal Reserve data: Yes (15 points) - H2s phrased as questions: Yes (10 points) - Last-updated date: No (0 points) - Named author: Yes (10 points) - Over 1,500 words: Yes (10 points) - Uses tables for rate comparisons: Yes (10 points)
Frequently asked questions
What are AI citations?
When you ask an AI engine (ChatGPT, Claude, Perplexity, Google AI Overviews) a question, it generates an answer and often lists the web pages it used as sources. These source attributions are AI citations. Pages that AI engines cite get referral traffic similar to ranking on the first page of traditional search results.
Does this tool contact AI engines to check if they cite my page?
No. The tool does not query any AI engine. It analyzes your content locally in your browser and scores it based on the structural signals that AI retrieval systems are known to look for. It predicts citation readiness, not actual citation status.
What is AEO (Answer Engine Optimization)?
AEO is the practice of structuring content so that AI-powered answer engines can easily extract, verify, and cite it. Where traditional SEO focuses on ranking in link-based search results, AEO focuses on appearing as a cited source in AI-generated answers. The two strategies overlap but have different structural requirements. Tracking this metric alongside conversion data gives a more complete picture of how changes affect actual business outcomes.
What score should I aim for?
A score of 80 or above indicates strong citation readiness. Most well-structured content with proper schema markup, source attribution, and a clear above-fold answer will score in the 75-90 range. A perfect 100 requires all 8 factors to be present, which is not always necessary or natural for every content type.
Which factor has the biggest impact?
The \\\\\\\"direct answer presence\\\\\\\" factor carries the highest weight at 20%. AI engines look for a clear, concise answer to the user's likely question in the first 40-60 words of the page. If your content buries the answer below the fold or behind an introduction, AI engines are less likely to extract and cite it.
Does structured data (JSON-LD) really affect AI citations?
Yes. FAQPage and HowTo schema provide machine-readable question-answer pairs and step-by-step instructions that AI retrieval systems can parse directly. Pages with structured data are easier for AI engines to index and cite because the data is explicitly labeled, not inferred from unstructured text.