quantum-random

Name: quantum-random
Availability: InStock
Author: 47Network

Generate quantum random bits, bytes, UUIDs, and entropy scores via API.

5|Updated Apr 15, 2026

Search Tags:#randomness #entropy #uuid #quantum #bit-generation #byte-generation

Ready to run

npx skills add https://github.com/47network/Sven --skill quantum-random

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: quantum-random
Source: https://github.com/47network/Sven/tree/main/skills/quantum/quantum-random
Command: npx skills add https://github.com/47network/Sven --skill quantum-random

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Generates high-entropy quantum random numbers for cryptographic and analytical tasks.

Core Features & Use Cases

Quantum-generated bits, bytes, and UUIDs with entropy metrics for secure token generation and testing.
Entropy analysis and quality assessment to verify randomness for simulations and data science workloads.
Use Case: When you need provably-random identifiers or cryptographic primitives in offline environments.

Quick Start

Request quantum random numbers by specifying the number of bits to receive bits, entropy, and metadata.

Frequently Asked Questions about quantum-random

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I generate high-entropy random numbers for cryptographic token generation?▼

This Skill generates high-entropy quantum random numbers using Hadamard-based measurement, providing bits, bytes, and UUIDs with entropy scores suitable for cryptographic primitives and secure token generation.

Can I generate UUIDs from quantum randomness for offline testing environments?▼

Yes, you can generate provably-random UUIDs from quantum randomness for offline environments by using the uuid API action, which outputs secure identifiers along with quality and entropy analysis metadata.

How does Hadamard-based measurement work for quantum bit generation?▼

Hadamard-based measurement for quantum bit generation works by applying quantum superposition principles to produce provably-random bits, which the API then validates and outputs with corresponding entropy scores for analytical tasks.

What is the best way to verify entropy quality in generated random bytes?▼

The best way to verify entropy quality in generated random bytes is to use the analyze API action, which conducts entropy analysis and quality assessment to validate randomness for simulations and data science workloads.

Are there limitations when using quantum random generation for large-scale simulations?▼

Limitations depend on specifying the correct number of bits in your request, as the system applies input validation and safety checks to ensure the generated bytes and entropy scores meet your simulation's requirements.