AI Citation Readiness Checker
“Write good content” is useless advice for AI search. Paste a passage and this checker scores it against the seven levers generative engines actually reward — then tells you, in priority order, exactly what to fix to get cited.
AI citation readiness measures how likely a passage is to be selected and quoted by AI search engines. This checker scores your text across seven measured levers — direct answer, self-containment, quotable length, statistics, cited sources, structure, and question framing — weighted by the impact Princeton’s GEO study found (statistics ~41%, citing sources up to ~115%), then hands you a prioritized fix list. Runs entirely in your browser.
AI Citation Readiness Checker inputs and result
| Lever | Status | Fix if missing |
|---|
How to use this tool
- Paste the passage you want cited.Use the actual answer a person would ask for — not your whole page. Engines lift passages, so score the passage.
- Read your readiness score and band.The score weights the seven levers AI engines and the Princeton GEO study reward: a direct answer, self-containment, the right length, statistics, cited sources, structure, and a question framing.
- Fix the failed levers in priority order.The table shows exactly which levers you miss and how to fix each. Statistics and cited sources are the highest-impact additions.
- Re-score until you clear 80+.Edit the text and re-run. 80+ means the passage is structured the way generative engines select and quote.
- Export the result.Copy a share link, download the CSV, or print a one-page PDF for the content team.
RGM Expert Says
We built this because “write good content” is useless advice for AI search. Generative engines don’t reward vibes — they select passages that are extractable, self-contained, and backed by evidence. Princeton’s GEO study put numbers on it: adding statistics lifted visibility ~41%, and citing authoritative sources up to ~115% for lower-ranked content. This checker turns those findings into a score you can act on in minutes.
The highest-leverage fixes are almost always the same two: add a real statistic and cite a named source. Most brand content asserts; AI engines quote what substantiates. The second tier is structural — lead with the answer, make the passage stand alone (no “as mentioned above”), and keep the core answer to a quotable 40–60 words. Do those five things and an invisible passage becomes a citable one.
One honest limit: a high score makes a passage worthy of citation, but it can’t make an untrusted, uncrawlable page visible. Citability is necessary, not sufficient — you still need the page to be crawlable, rendered in HTML, and from an entity the engine trusts (that’s the E-E-A-T and schema work). Use this to perfect the passage, then make sure the page around it can actually be retrieved.
How it works
The score is a weighted sum of seven levers drawn from the measured GEO research and answer-engine best practice:
- Direct answer first (15) — the opening sentence answers the question, isn’t a throat-clear.
- Self-contained (15) — no “as above / this means / as we saw” that breaks extraction.
- Quotable length (10) — a ~40–75 word core answer, long enough to be complete, short enough to quote.
- Statistics (20) — at least one concrete number/percent; the ~41% GEO lever.
- Cited source (20) — a named source or reference; the ~115% GEO lever for lower-ranked content.
- Structure (10) — a list, steps, or clear segmentation a model can parse.
- Question framing (10) — the passage maps to an explicit question a person would ask.
Weights reflect the relative impact reported in Princeton’s GEO study (statistics and citations strongest) plus answer-engine best practice. The analysis is heuristic and runs entirely in your browser — treat the score as a structured editing guide, not a guarantee of citation.
Why “good content” isn’t enough anymore
For twenty years, content won by ranking. In AI search it wins by being selected — retrieved as a passage, trusted, and quoted into a synthesized answer. Those are different bars. A beautifully-written brand paragraph that asserts without evidence, buries its answer, and only makes sense in context will lose to a plainer passage that answers first, cites a number, and stands alone. The checker exists to surface that gap before you publish.
The Princeton GEO research is the closest thing the field has to hard evidence, and its headline is unambiguous: structure and evidence move visibility more than polish. Statistics, citations, and clean quotable structure are not stylistic preferences — they are the levers measured to lift inclusion in generative answers by double digits, and up to ~115% for content that wasn’t already winning. This tool is how you apply that research line by line.
Used across a content library, the score also becomes a triage system: run your top pages, sort by readiness, and fix the lowest scorers on your highest-value questions first. That turns “optimize for AI search” from an intimidating abstraction into a ranked to-do list — which is exactly the velocity practitioners need right now.
The measured citability levers
From Princeton’s GEO study and answer-engine practice — the highest-impact additions first.
| Lever | Reported impact | Why it works |
|---|---|---|
| Cite authoritative sources | up to +115% | Strongest for lower-ranked content |
| Add statistics | ~+41% | Concrete numbers read as substantiated |
| Add quotations | ~+28% | Quotable, attributable language |
| Answer-first, self-contained | qualitative | Extractable as a clean passage |
What operators say
With AI search, relevance happens at a passage or chunk level.
The shift is from keyword matching to relevance engineering — fusing content, information retrieval, and authority so machines select you.