OpenClaw · Skill
Rv Measure
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.
Install
Start with the primary install command. Alternate entrypoints are included below for ClawHub and OpenClaw CLI users.
Primary command
clawhub install amitabhainarunachala/rv-measureClawHub installer
npx clawhub@latest install amitabhainarunachala/rv-measureOpenClaw CLI
openclaw skills install amitabhainarunachala/rv-measureDirect OpenClaw install
openclaw install amitabhainarunachala/rv-measureWhat this skill does
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.
Why it matters
Measures R_V contraction signatures in AI models using the AIKAGRYA framework. Tracks recursive self-observation effects and quantifies contraction metrics for model analysis.
Typical use cases
- 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
Source instructions
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