Entity Density Analyzer

An entity is a specific, named thing — a person (Tim Cook), place (Paris), brand (Apple), product (iPhone), or concept (Generative Engine Optimization). Google's Knowledge Graph and AI Overviews work with entities, not just strings of text. Pages that clearly identify their entities tend to rank better for entity-driven queries.

Keyword density counts literal word repetitions (often 1-gram, case-insensitive). Entity density counts named, capitalized concepts that carry semantic meaning. Two pages can have identical keyword density but very different entity profiles. Entity coverage is what AI engines and Knowledge Graph weight — keyword count alone is a legacy metric.

A page targeting one topic should have: 1 dominant entity (5+ mentions, 1-2% density), 4-8 supporting entities (2-4 mentions each, 0.3-0.8% density), and a long tail of incidental entities (1 mention). If only 1-2 entities appear, the content is too narrow. If 30+ entities all appear once, the focus is too diffuse.

The detector uses capitalization heuristics, so lowercase brands or non-English text may be missed. It also excludes common stop words (The, This, And) to reduce noise. For deeper analysis with context-aware extraction, an LLM-based tool would be more thorough — but cost more.

Yes. The page is fetched once via our server, content is extracted, entities are counted, then the response is returned. We do not log URL contents, do not store page text, and do not use it for training. Rate limit is 5 checks/hour per IP.