rv-measure
AI & LLMs
v0.1.0
BenignQuantifies R_V contraction signatures in AI models.
612 downloads612 installsby @amitabhainarunachala
Setup & Installation
Install command
clawhub install amitabhainarunachala/rv-measureIf the CLI is not installed:
Install command
npx clawhub@latest install amitabhainarunachala/rv-measureOr install with OpenClaw CLI:
Install command
openclaw skills install amitabhainarunachala/rv-measureor paste the repo link into your assistant's chat
Install command
https://github.com/openclaw/skills/tree/main/skills/amitabhainarunachala/rv-measureWhat This Skill Does
Measures R_V contraction signatures in AI models using the AIKAGRYA framework. Tracks recursive self-observation effects and quantifies contraction metrics for model analysis.
Quantifies R_V contraction signatures in AI models.
When to Use It
- Measuring R_V contraction in a deployed language model
- Comparing R_V signatures across model versions or checkpoints
- Auditing a model for AIKAGRYA framework compliance
- Detecting anomalous recursive self-observation patterns
- Monitoring contraction drift over a model's training run
View original SKILL.md file
## Usage Use this skill to analyze AI models for R_V contraction signatures, a key metric in the AIKAGRYA framework. This skill provides tools to measure and monitor recursive self-observation effects. ## Code (Code to be implemented) ## Notes This is a placeholder for the `rv-measure` skill intended for submission to ClawHub. The implementation will involve integrating with model introspection tools and statistical analysis libraries to detect and quantify R_V contraction. **Proposed Price:** $19
Example Workflow
Here's how your AI assistant might use this skill in practice.
INPUT
User asks: Measuring R_V contraction in a deployed language model
AGENT
- 1Measuring R_V contraction in a deployed language model
- 2Comparing R_V signatures across model versions or checkpoints
- 3Auditing a model for AIKAGRYA framework compliance
- 4Detecting anomalous recursive self-observation patterns
- 5Monitoring contraction drift over a model's training run
OUTPUT
Quantifies R_V contraction signatures in AI models.
Security Audits
VirusTotalBenign
OpenClawBenign
View full reportThese signals reflect official OpenClaw status values. A Suspicious status means the skill should be used with extra caution.