Which AI models does the GCR Index score for?

The GCR Index scorer evaluates citation readiness for ChatGPT (GPT-4o), Gemini, Perplexity, Claude (Claude 3.7), DeepSeek, Mistral, and Meta AI. The scoring methodology is developed from analysis of structural patterns that influence AI citation across major generative engines.

Is the GCR Index scorer free to use?

Yes. The GCR Index scorer is free to use, requires no registration, and needs no API key. It is an open research initiative.

What does a high GCR score mean?

A high GCR score (70–100) indicates that your content has strong structural and semantic properties that make it likely to be cited by AI systems. This includes high information density, explicit factual anchoring, clear Q→A heading structure, and low keyword stuffing.

How is the GCR Index different from traditional SEO?

Traditional SEO optimizes for search engine ranking (PageRank, backlinks, keyword density). The GCR Index optimizes for AI citation readiness: how likely an LLM is to retrieve and cite your content as a source. It focuses on semantic density, entity salience, and extractability.

GCR Index

GCR Index is the benchmarking layer for GEO-ready content. Score citation readiness for ChatGPT, Gemini, Perplexity, Claude, DeepSeek, and Meta AI.

The composite formula (v2.5.15) is: GCR = 0.55×GeoContent + 0.20×AICitability + 0.15×TopicalAuthority + 0.10×Readability. The four dimensions contain 15 sub-metrics: D1 (7 content structure metrics: sentence autonomy, information density, factual anchoring, fanout query coverage, navigation clarity, semantic uniqueness, and duplicate prevention), D2 (5 citability signals: statistics, entity naming, answer proximity, Q→A headings, keyword discipline), D3 (3 topical authority metrics: Google Suggest coverage, semantic co-occurrence, PAA question coverage), D4 (3 readability metrics: Flesch-Kincaid grade, sentence variety, vocabulary complexity).

The scoring methodology is transparent, research-backed, and free to use. No registration required. Developed from a corpus of 1,247+ articles.

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