Content Scoring: How AI Ranks Your Content Quality

What is a Content Score?

A Content Score is a 0-100 measure of traditional SEO quality for a piece of content. It is composed of weighted signals across seven dimensions: term frequency, entity coverage, heading structure, word count, readability, internal links, and GEO signals. No single signal determines the score - the weight of each signal reflects its empirical impact on ranking outcomes across the content corpus.

The Seven Content Score Signals

• Term Frequency: Keyword prominence in the correct positions - title, H1, first paragraph. Not keyword stuffing; correct structural placement.
• Entity Coverage: How many topically relevant entities appear relative to what a well-covering treatment of the subject would include.
• Heading Structure: Logical H1-H3 hierarchy. One H1, sub-topics in H2, details in H3. Flat or inverted hierarchies penalize structure.
• Word Count: Coverage sufficient to answer the target query. Not longer for its own sake; long enough to cover entities and sub-questions.
• Readability: Flesch-Kincaid grade level optimized for the target audience. Expert topics tolerate higher grade levels.
• Internal Links: Contextual links to supporting content that consolidate link equity and prevent orphan pages.
• GEO Signals: Factual density and answer-first formatting, which contribute to both Content Score and GEO Score simultaneously.

The Review Gate

The Review Gate is a server-enforced checkpoint that blocks publishing of Articles with a Content Score below 70/100. Writers receive an ExplainScore breakdown - not a raw number, but a ranked list of the exact signals that failed and the specific changes that would fix them. This turns content scoring from a vanity metric into an editorial workflow tool.