goldenseed
Deterministic entropy streams for reproducible testing and procedural generation.
Setup & Installation
Install command
clawhub install beanapologist/goldenseedIf the CLI is not installed:
Install command
npx clawhub@latest install beanapologist/goldenseedOr install with OpenClaw CLI:
Install command
openclaw skills install beanapologist/goldenseedor paste the repo link into your assistant's chat
Install command
https://github.com/openclaw/skills/tree/main/skills/beanapologist/goldenseedWhat 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.
User asks: Debugging flaky tests by replaying the exact random sequence that caused a failure
- 1Debugging flaky tests by replaying the exact random sequence that caused a failure
- 2Generating identical game worlds or map chunks from a shared numeric seed
- 3Running reproducible Monte Carlo simulations with verifiable byte-level results
- 4Creating procedural art or generative NFTs where the seed proves the output
- 5Proving fair dice rolls in competitive games by publishing the seed after the fact
Deterministic entropy streams for reproducible testing and procedural generation.
Security Audits
These signals reflect official OpenClaw status values. A Suspicious status means the skill should be used with extra caution.
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