Geometry Skill - Shape-Attribution & MACA Consensus

Community

Encode concepts geometrically, achieve consensus.

AuthorPOWERFULMOVES
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill enables advanced reasoning by encoding complex concepts into mathematical shapes and facilitating multi-agent consensus, even in bandwidth-constrained environments.

Core Features & Use Cases

  • Shape-Attribution Pipeline: Transforms diverse data into standardized geometric representations (Geometry Packets).
  • CHIT Geometry Bus: Enables bandwidth-efficient inter-agent communication using compressed holographic data.
  • MACA Consensus: Achieves multi-agent agreement based on entropy reduction and geometric transformations.
  • Use Case: Coordinate a swarm of drones by representing their spatial relationships as geometric shapes, allowing them to reach a consensus on optimal formation for a complex maneuver with minimal communication overhead.

Quick Start

Use the geometry skill to attribute market trend data as a timeseries geometry packet.

Dependency Matrix

Required Modules

None required

Components

references

💻 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: Geometry Skill - Shape-Attribution & MACA Consensus
Download link: https://github.com/POWERFULMOVES/PMOVES-BoTZ/archive/main.zip#geometry-skill-shape-attribution-maca-consensus

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