Skip to main content

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: geo-score-demo.onrender.com (may take ~30s to wake up on first visit)

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

Release files for geo-score-core 0.1.4

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for geo-score-core 0.1.4
File Size Uploaded
geo_score_core-0.1.4.tar.gz 10.9 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for geo-score-core 0.1.4
File Interpreter ABI Platform
geo_score_core-0.1.4-py3-none-any.whl Python 3 none any Details

Total release size: 21.0 kB

Release files / geo_score_core-0.1.4.tar.gz

Download URL geo_score_core-0.1.4.tar.gz
Size 10.9 kB
Tags Source
SHA-256 checksum
How to use checksums
883373c354700e52388bf34fb34c48cb0eed0631acd4cbf0f8f3bb197d3906fd
BLAKE2b-256 checksum
How to use checksums
d08515d6e21902f2ccccfe481a30d7abdf483d809552ec2619aafb50f0627f04
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.13.9

Release files / geo_score_core-0.1.4-py3-none-any.whl

Download URL geo_score_core-0.1.4-py3-none-any.whl
Size 10.2 kB
Tags Python 3
SHA-256 checksum
How to use checksums
9e78aa788cc0416390ba6c3ef6b22ee14e7c39622494b5c335f70fe538e88d34
BLAKE2b-256 checksum
How to use checksums
f9c5d364ec3ba8d513fb67575155a19807e5e012b59926ace4a6ace867547aad
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.13.9

Release history Release notifications | RSS feed

This release

0.1.4 This release

2 release files

0.1.3

2 release files

0.1.1

2 release files

0.1.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page