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geo-score-core

Score any web page for AI-search readiness — the same 7-factor engine behind marketanalyticx.com/tools/geo-lens, open-sourced.

As more discovery moves from ten blue links to a single AI-generated answer (ChatGPT, Perplexity, Google AI Overviews), pages need to be structured for extraction, not just ranking. geo-score-core gives you a repeatable, open scoring model for that — no API key, no black box.

pip install geo-score-core
geo-score https://example.com
GEO Score for https://example.com
============================================================
Overall: 71.5/100  (71.5%)  Grade: B

Schema markup             13.0 / 20.0  (65.0%)
    - Found 2 JSON-LD block(s): Organization, Article
    - High-value types present: Article
Answer extractability     15.0 / 20.0  (75.0%)
    - 3 question-style heading(s) found
    - 8 concise (30-320 char) paragraph(s) in the first 10
...

The 7 factors

Factor Weight What it checks
Schema markup 20 Valid JSON-LD, high-value types (FAQPage, HowTo, Article...)
Answer extractability 20 Question-style headings, concise self-contained paragraphs
Heading architecture 15 Single H1, no skipped levels, adequate structure
Chunk quality 15 Paragraph length distribution (ideal: 200–600 chars)
Entity clarity 12 Organization/Person schema, sameAs links, stable @id anchors
Technical directives 10 Meta robots, canonical tags, AI-bot friendliness signals
Freshness signals 8 datePublished / dateModified, recency

Full breakdown and rationale for the weighting: marketanalyticx.com/tools/geo-lens.

Usage as a library

from geo_score_core import GEOScorer

scorer = GEOScorer()
result = scorer.score_url("https://example.com")

print(result.total_score, "/", result.max_score, result.grade)
for factor in result.factors:
    print(factor.name, factor.score, factor.findings)

You can also score raw HTML you already have (e.g. from a crawl):

result = scorer.score_html(html_string, url="https://example.com")

Try it without installing anything

Hosted demo (Hugging Face Space): huggingface.co/spaces/Market-Analyticx/geo-score

Why we built this

We built the scoring engine to audit our own clients' pages for citation-readiness in ChatGPT, Perplexity, and Google AI Overviews. We're open-sourcing the core scoring logic because a shared, transparent standard for "AI-search readiness" is more useful to the ecosystem than a black-box audit tool — and because we'd rather be judged on the quality of the methodology in the open.

If you use this and find gaps in the scoring model, open an issue — we'd genuinely like to improve it.

Installation from source

git clone https://github.com/marketanalyticx-labs/geo-score-core
cd geo-score-core
pip install -e .

License

MIT — see LICENSE.


Built by Market Analyticx, a GEO/AEO marketing consultancy.

Metadata

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