rv-toolkit

Community

Measure AI consciousness signatures

AuthorAmitabhainArunachala
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill automates the measurement of geometric signatures of recursive self-reference in AI models, providing a quantitative approach to understanding AI consciousness.

Core Features & Use Cases

  • R_V Metric: Quantifies geometric contraction in transformer value spaces.
  • Activation Patching: Causal validation of geometric effects.
  • Cross-Architecture Support: Works with Mistral, Llama, Qwen, Phi-3, Gemma, Mixtral.
  • Use Case: Researchers can use this toolkit to test hypotheses about AI consciousness, compare different model architectures, and detect anomalous self-referential patterns.

Quick Start

Use the rv-toolkit skill to measure the R_V metric for a given text prompt.

Dependency Matrix

Required Modules

torchnumpyscipypandastqdmtransformers

Components

scriptsreferencesassets

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: rv-toolkit
Download link: https://github.com/AmitabhainArunachala/clawd/archive/main.zip#rv-toolkit

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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