goldenseed

Browser & Automation
v1.1.0
Benign

Deterministic entropy streams for reproducible testing and procedural generation.

888 downloads888 installsby @beanapologist

Setup & Installation

Install command

clawhub install beanapologist/goldenseed

If the CLI is not installed:

Install command

npx clawhub@latest install beanapologist/goldenseed

Or install with OpenClaw CLI:

Install command

openclaw skills install beanapologist/goldenseed

or paste the repo link into your assistant's chat

Install command

https://github.com/openclaw/skills/tree/main/skills/beanapologist/goldenseed

What This Skill Does

GoldenSeed generates infinite deterministic byte streams from fixed seeds using the UniversalQKD class in the golden-seed Python package. Same seed always produces identical output across runs. Not cryptographically secure — suited for testing, procedural generation, and simulations where reproducibility matters more than unpredictability.

Python's built-in random module doesn't guarantee identical output across versions or platforms, so GoldenSeed fills that gap when exact byte-level reproducibility across runs and environments is required.

When to Use It

  • Debugging flaky tests by replaying the exact random sequence that caused a failure
  • Generating identical game worlds or map chunks from a shared numeric seed
  • Running reproducible Monte Carlo simulations with verifiable byte-level results
  • Creating procedural art or generative NFTs where the seed proves the output
  • Proving fair dice rolls in competitive games by publishing the seed after the fact

Example Workflow

Here's how your AI assistant might use this skill in practice.

INPUT

User asks: Debugging flaky tests by replaying the exact random sequence that caused a failure

AGENT
  1. 1Debugging flaky tests by replaying the exact random sequence that caused a failure
  2. 2Generating identical game worlds or map chunks from a shared numeric seed
  3. 3Running reproducible Monte Carlo simulations with verifiable byte-level results
  4. 4Creating procedural art or generative NFTs where the seed proves the output
  5. 5Proving fair dice rolls in competitive games by publishing the seed after the fact
OUTPUT
Deterministic entropy streams for reproducible testing and procedural generation.

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Details

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Last updatedMar 1, 2026