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Every score in the product comes from one canonical model. These are the concepts that model exposes.
Content Score is a 0–100 measure of how well a draft matches the traditional Google ranking surface for a target keyword. It weights seven signals: term frequency, entity coverage, heading structure, word count, readability, internal links, and GEO signals. No single signal determines the score — each weight reflects its empirical impact on ranking outcomes.
GEO Score is a 0–100 measure of how ready a draft is for AI retrieval, citation, and answer extraction. It weights five signals: Entity Authority, Factual Density, Answer-First Formatting, Source Credibility, and Freshness. Where Content Score targets document ranking, GEO Score targets passage-level extraction by AI search engines.
The Review Gate is a server-enforced checkpoint that blocks publishing of articles with a Content Score below 70/100 AND a GEO Score below 70/100. Writers receive an ExplainScore breakdown — the ranked list of signals that failed and the specific changes that would raise the score above the threshold.
The Action Rail prioritizes the changes most likely to move a score and explains which signal each action affects, so editors fix the highest-impact issues first instead of guessing.