What is an involution in the context of this Claude Code skill?

An involution is a mathematical transformation that is its own inverse (ι ∘ ι = id). In this skill, it ensures that switching from one perspective to another and back returns to the exact original state, maintaining frame-invariant structures.

How does this skill handle multi-agent systems?

It uses best-response dynamics to reach a Nash equilibrium where each agent's state is the optimal response to others, ensuring the system reaches a stable fixed point regardless of the observer's frame.

How is GF(3) conservation used?

GF(3) conservation is used in triadic games (like 3-MATCH) to ensure that the sum of states (trits) equals zero, providing a mathematical anchor for equilibrium and compositional coherence.

What is 'Unworlding'?

Unworlding is the process of extracting the underlying structural pattern from a specific interaction or demo while ignoring the specific evaluation context, allowing the logic to be applied universally.

Unworlding Involution Framework

Name: Unworlding Involution Framework
Author: plurigrid

byplurigrid

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Data Science & ML

Implements frame-invariant self-inverse derivation patterns using GF(3) conservation and triadic color dynamics.

About

The Unworlding Involution skill provides a sophisticated mathematical framework for extracting frame-invariant structures from complex interaction dynamics. By leveraging the principle of involution—transformations that serve as their own inverse—it allows Claude to maintain stable identity and equilibrium across varying perspectives. This skill is essential for developers working with multi-agent systems, Perceptual Control Theory (PCT), and triadic logic, offering a robust way to model best-response dynamics and Nash equilibria where the 'self' remains invariant under observation.

Key Features

Hierarchical mapping based on Perceptual Control Theory (PCT)
Frame-invariant self-extraction from interaction dynamics
2 GitHub stars
Self-inverse derivation patterns where applying a transformation twice returns the identity
Loopy strange fixed-point generation for generator-observer symmetry
GF(3) conserved triadic color game logic and Nash equilibrium modeling

Use Cases

Implementing compositional coherence in triadic logic and topological computing environments
Developing frame-invariant AI observation systems that maintain consistency across perspectives
Modeling stable multi-agent interactions in game theory and AI simulations

About

Key Features

Hierarchical mapping based on Perceptual Control Theory (PCT)
Frame-invariant self-extraction from interaction dynamics
2 GitHub stars
Self-inverse derivation patterns where applying a transformation twice returns the identity
Loopy strange fixed-point generation for generator-observer symmetry
GF(3) conserved triadic color game logic and Nash equilibrium modeling

Use Cases

Implementing compositional coherence in triadic logic and topological computing environments
Developing frame-invariant AI observation systems that maintain consistency across perspectives
Modeling stable multi-agent interactions in game theory and AI simulations