A very small CLI helper that compares three conceptual Web3 styles and shows how well each fits your priorities:
- Aztec-style zk rollup (privacy-heavy, zk circuits over Ethereum)
- Zama-style FHE stack (encrypted compute with fully homomorphic encryption)
- Soundness-first protocol (formal proofs and high correctness)
The script does not connect to a blockchain and has no external dependencies. It is just a tiny scoring function that helps you think about where your project sits in the space between privacy, soundness, and UX speed.
Repository layout
This repo intentionally has only two files:
- app.py
- README.md
Concept
You provide three numbers between 0 and 10:
- privacy importance
- soundness / proofs importance
- UX speed importance
For each style, the script stores three floats between 0 and 1:
- privacy
- soundness
- ux_speed
It then computes a simple fit score between 0.0 and 1.0 by comparing your needs to each profile and prints a mini bar chart and label (excellent, good, ok, weak).
Installation
Requirements:
- Python 3.8 or newer
- No extra packages
Steps:
- Create a new GitHub repository.
- Place app.py and README.md in the root directory.
- Ensure the python command is available in your shell.
- Mark app.py as executable if you want (optional).
Usage
Run from the repository root.
Default run (uses built-in defaults):
python app.py
Example: strong privacy, strong soundness, moderate speed:
python app.py --privacy 9 --soundness 9 --speed 6
Example: high UX speed, moderate privacy, strong soundness:
python app.py --privacy 6 --soundness 8 --speed 9
Example: FHE-heavy, privacy-maximal project that accepts slower UX:
python app.py --privacy 10 --soundness 9 --speed 3
Output
The script prints:
- your stated needs for privacy, soundness, and UX speed
- one line per style with:
- name and key
- numeric fit score between 0.0 and 1.0
- textual label (excellent, good, ok, weak)
- a small bar made of █ characters
- a short explanatory note
All numbers are illustrative and subjective. The tool is meant to help guide conversation about whether your design is closer to an Aztec-like zk rollup, a Zama-like FHE compute stack, or a soundness-first protocol approach. You can edit the style values in app.py to better match your own views.