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PythonReactSEOPDF
OpenClaw

rv-measure

Quantifies R_V contraction signatures in AI models.

amitabhainarunachala0 installations selon la source☆ 0 Étoiles du dépôtv0.1.0

Installation

Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.

SkillHub CLI

skillhub install amitabhainarunachala/rv-measure

Examinez la source et la compatibilité, puis suivez les étapes d’installation.

Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.

Voir la source ↗Guides

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

Informations sur la source

Source
github
Repository
openclaw/skills
Path
skills/amitabhainarunachala/rv-measure
Version
0.1.0
Commit
46135a6409355b938b32ee6f9e69fb5fcaec4516
Source de classification
rules
Statut
active
Visibilité
public

Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.

Contenu extrait

SKILL.md
## 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

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