How We Score

AI Citation Checker grades content on a 100-point scale across six criteria. Each criterion targets a signal that AI search engines — Perplexity, ChatGPT Search, Google Gemini, Claude, Grok, and others — demonstrably use when deciding which passages to extract and cite.

The six criteria

Extractable Claims — 25 points

Does the content contain self-contained factual claims an AI can lift directly without surrounding context? Specific, verifiable assertions score highest. Vague statements, throat-clearing introductions, and opinion without evidence score zero. This is the single biggest factor because AI engines need a quotable unit of information.

Evidence Density — 25 points

How many specific statistics, dates, named sources, and proper nouns appear per thousand words? Patterns like "According to [Source] in [Year]..." score highest. Phrases like "studies show" or "experts say" score zero. Concrete evidence signals authority to AI retrieval systems.

Entity Clarity — 20 points

Are subjects named explicitly rather than referenced with pronouns? AI systems resolve entity references when indexing, and content that repeatedly uses canonical entity names ("OpenAI", "Perplexity") rather than "they" or "it" is easier to index correctly and more likely to be retrieved for relevant queries.

Passage Independence — 15 points

Can each paragraph stand alone without needing the surrounding context to make sense? AI retrieval systems chunk content into passages. Paragraphs that rely on earlier setup ("As we mentioned above...") lose points because they break when extracted in isolation.

Information Structure — 10 points

Does the content use headers, bullet points, numbered lists, or comparison tables? Scannable structure lets AI engines chunk and index content more accurately. Long, unbroken prose is harder to extract cleanly. Short paragraphs (under three sentences) score better than long ones.

Freshness Signals — 5 points

Does the content include recent dates, current statistics, or timely references? AI engines prefer citing content that signals it reflects current information. A post that mentions "as of Q1 2026" or cites a 2025 study signals relevance in a way that undated content cannot.

Score tiers

Total scores map to four performance tiers:

• 90–100 — Strong. Content is well-structured for AI citation. AI engines are likely to extract passages from it for relevant queries.
• 70–89 — Good. Solid GEO foundation with minor gaps. Addressing the flagged weaknesses will push it into the top tier.
• 40–69 — Needs Work. The content has citation potential but is missing key signals. Follow the recommended fixes in your results.
• 0–39 — Poor. Significant structural or evidence gaps. AI engines are unlikely to cite this content in its current form.

How the analysis works

When you submit a URL, we fetch the page content using Jina Reader and a direct fallback. Pasted text is used as-is. The cleaned text (up to 8,000 characters) is sent to Google Gemini with a structured rubric prompt. Gemini returns sub-scores for each criterion plus an AI snippet prediction, a list of critical gaps, and — for scores below 70 — a rewritten opening paragraph optimized for citation.

All sub-scores are capped server-side at their declared maximums before the total is computed. If Gemini is unavailable, a deterministic fallback scorer runs locally using text pattern analysis.

Accuracy and limitations

The score is a strong directional signal, not a guarantee. AI citation also depends on query relevance, domain authority, and the competitive set of sources an AI engine considers for a given query — factors our rubric cannot measure. Use your score to identify structural weaknesses, not to predict exact citation frequency.

Questions about your score?

Email us at contact [at] aicitationchecker.comCopy