The DirJournal Information Density Grader is an Answer Engine Optimization (AEO) tool that calculates the ratio of hard facts to filler text, ensuring content is primed for AI extraction.
Paste text above (or click Load sample) to see the Information Density Score and inline highlights.
LLMs prioritize citing dense, factual structures over verbose marketing copy — a sentence with a name, a date, and a number is far more likely to be quoted in an AI answer than a paragraph of adjective-heavy filler.
Density is also a proxy for trust: when an answer engine has to choose between a vague page and a specific page on the same topic, the specific page wins because its claims are individually verifiable.
The Information Density Score is the ratio of hard entities (proper nouns, dates, numbers, statistics) to total word count, scaled to 0-100. Marketing copy typically scores under 20; news reporting lands in the 40-60 range; reference and encyclopedia writing tends to score 70+. A higher score means more citable facts per sentence and a smaller gap between what the page says and what an answer engine can quote back.
Replace flagged filler words (utilize, leverage, delve, robust, seamless, paramount) with the concrete verb they're masking, drop weakening adverbs (very, really, basically), and rewrite passive constructions into active voice. Then add the missing facts: who, when, how much, where. Every replaced fluff word should become a name, a date, a number, or a verifiable claim — that is what raises the score.