See your website the way a first-time visitor does.
Mona predicts where eyes land on a web page, how the brain reacts, checks readability, and gives a score out of 100.
A small desktop app: the AI models run on your PC, nothing is sent anywhere.
Français · Website · Measurements · AI models · Architecture · Terms · Privacy
- Gaze prediction: a heat map of where people look first, from two AI models trained on real eye-tracking data (62 people, 1,980 interfaces).
- Brain reaction: an estimate of how 20 visual areas of the cortex respond (indicative, trained on fMRI data).
- Readability score: six checks (text contrast, text size, main button visibility, visual hierarchy, amount of text, clutter) combined into a score out of 100, with advice for each screen.
- UI element detector: finds text, buttons, images, fields and icons on any screenshot, mockup or Figma export.
- A real Chrome does the looking: paste an address, and Mona opens a test Chrome, scrolls the page to the very bottom like a visitor, and reads it. Or drop an image.
- Adapts to your PC: Mona reads your processor, memory and graphics card first, then picks how hard to work (and leaves a quarter of your cores free).
- Private by design: no account, no tracking. The only network traffic is the visit to the site you analyze.
You need Python 3.10 or newer. Download the ZIP (the AI models are inside) or clone the repository, then:
| Windows | double-click Mona.bat |
| macOS, Linux | run ./mona.sh |
The first time, it installs everything (a few minutes: Python packages and the test Chrome, about 150 MB). After that the app opens straight away, in its own window.
Or by hand
pip install -r requirements.txt
python -m mona setup # installs the test Chrome, once
python -m mona # opens the appFor a native window instead of a Chrome/Edge app window: pip install -r requirements-app.txt.
python -m mona # open the app
python -m mona analyze https://example.com # analyze without the interface
python -m mona analyze screenshot.png # analyze an image
python -m mona doctor # your PC, the settings Mona chose, the state of the models
python -m mona setup # install the test Chrome
python -m mona serve # server only, no window
python -m pytest # run the testsEnvironment variables: MONA_PORT, MONA_MAX_SCREENS (default 12), MONA_HEADLESS=1 (hide the test Chrome), MONA_HOME (where settings are stored).
mona-local/
├── models/ ← THE AI MODELS (*.onnx) + MODELS.json → docs/MODELS.md
├── mona/
│ ├── ai/ run the models: gaze, brain, detector, plan B
│ ├── capture.py the test Chrome: open, scroll, capture
│ ├── rules.py six readability rules and the score
│ ├── pipeline.py, server.py, desktop.py, hardware.py
│ └── web/ the interface
├── docs/ ARCHITECTURE.md, MODELS.md
├── tests/ automatic tests
├── Mona.bat · mona.sh one-click launchers
└── LICENSE, TERMS.md, PRIVACY.md, NOTICE.md
- The AI models are in
models/and ship with the repository.docs/MODELS.mdexplains each one: role, input and output, training data, licenses. - How the parts fit together:
docs/ARCHITECTURE.md.
Measured on cases never seen during training:
| What | Result |
|---|---|
| Gaze vs. real eye-tracking (UEyes) | correlation 0.68 |
| Gaze on web pages from another dataset (Imp1k) | correlation 0.56 |
| Element detector (text, button, image) | F1 0.64 |
| Score from an image alone vs. from the page code | 5.5 points out of 100 apart on average |
The brain model comes from a single subject: an indication, not a diagnosis. Mona measures readability and attention, not taste, and it does not replace a test with real people or an accessibility audit. Details and method: https://mona.devliam.com/benchmarks.html.
Is it free? Yes, for personal, non-commercial use. See the license below.
Does it work on a phone? No, it is a desktop app (Windows, macOS, Linux).
Is it fast? On a recent PC, an image takes a few seconds and a page about ten seconds. python -m mona doctor shows what Mona chose for your machine.
Can I use it for client work or in my product? Not without written permission from the author. See LICENSE.
Where do my reports go? Nowhere: they stay in the app's own storage on your PC. You can export them as JSON or print them to PDF.
Mona Personal Use License (LICENSE, with French translation): use it for yourself, for free. No redistribution, no selling, no use to make money (including client work and online services), no training other models with it, and a visible credit ("Mona by Liam DB") whenever you show or publish something that uses it. It is source-available, not open source. For anything else, ask the author first.
- Terms of use · Privacy policy · Third-party data and licenses
- Training data and pretrained weights have their own terms; the brain model derives from research-only images and is for non-commercial research use.
- To cite Mona, use the "Cite this repository" button on GitHub (CITATION.cff).
Keywords: web page analysis, visual saliency, eye-tracking prediction, attention heat map, UX audit, readability score, WCAG contrast, Figma mockup analysis, UI element detection, ONNX, Playwright, desktop app.