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RUNE Prompt Amplification

Transforms any flat prompt into a structured 8-layer XML prompt using RUNE's semantic engine — delivering ~45% higher quality AI responses. Built on Spinoza'...
使用RUNE语义引擎将任何扁平提示转换为结构化8层XML提示,提供约45%更高质量的AI响应。基于Spinoza...
mrsarac
AI智能 clawhub v1.0.0 1 版本 100000 Key: 需要
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概述

RUNE — Prompt Amplification Framework

RUNE transforms flat, ambiguous prompts into structured XML prompts validated by Spinoza's philosophical framework — resulting in outputs that are ~45% higher quality than raw prompting.

The 8 Layers

LayerNamePurpose
----------------------
L0System CoreRole, persona, behavioral rules
L1Context IdentityDomain knowledge, target audience
L2Intent ScopeTask definition, output format
L3GovernanceConstraints, ethical boundaries
L4Cognitive EngineThinking strategy (CoT, ToT)
L5Capabilities DomainTools, integrations, capabilities
L6QAValidation criteria, quality control
L7Output MetaFormat, style, length, language

Requirements

  • Python 3.11+
  • RUNE repo cloned locally
  • RUNE_API_KEY in ~/.secrets

Usage

# Pipe a prompt
echo "Write a blog post about AI" | bash main.sh

# Pass as argument
bash main.sh "Explain quantum entanglement to a 12-year-old"

Setup

# 1. Clone RUNE repo
git clone https://github.com/mrsarac/master-prompts ~/Documents/GitHub/rune

# 2. Add API key to ~/.secrets
echo "export RUNE_API_KEY=your_key" >> ~/.secrets

# 3. Test
echo "Hello" | bash main.sh

Source

  • Author: NeuraByte Labs
  • Version: RUNE v4.3 / WAND v1.5.0
  • Repo: https://github.com/neurabytelabs/rune-skill

版本历史

共 1 个版本

  • v1.0.0 当前
    2026-03-30 04:47 安全 安全

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腾讯云安全 (Keen)

安全,无风险
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腾讯云安全 (Sanbu)

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