What are Observational Bridges?

They are synchronization strategies that allow different versions of skills to map to one another, resolving conflicts through multi-dimensional cubical logic.

What is a Bisimulation Game in AI development?

It is a formal framework used to ensure two systems are functionally indistinguishable by testing transitions and observations across different agents.

Which AI agents are supported by this skill?

The protocol specifically targets cross-platform dispersal for Claude, GitHub Codex, and Cursor, while maintaining a central source of truth.

How does GF(3) conservation help with skill dispersal?

It uses ternary logic (-1, 0, +1) to ensure that moves made by Attacker, Defender, and Arbiter roles remain balanced, preventing state corruption during synchronization.

Bisimulation Game

Name: Bisimulation Game
Author: plurigrid

byplurigrid

•

开发者工具

Synchronizes and disperses resilient skills across AI agent ecosystems using ternary conservation and observational equivalence.

关于

The Bisimulation Game skill provides a sophisticated topological framework for maintaining functional equivalence across multiple AI agents like Claude, Codex, and Cursor. By utilizing GF(3) conservation laws and category theory-based observational bridges, it ensures that skill updates are propagated reliably without losing state integrity. This skill is essential for developers managing complex multi-agent workflows who require formal verification of agent behavior and resilient, self-rewriting capability dispersal.

主要功能

Multi-agent skill dispersal protocol (Claude, Codex, Cursor)
2 GitHub stars
Observational bridge types for version-aware synchronization
Self-rewriting capabilities via MCP Tasks integration
Automated bisimulation verification and conflict resolution
GF(3) ternary logic conservation for state transitions

使用场景

Automating the discovery and propagation of new skills from web resources to local agent directories
Verifying that updated agent versions remain functionally equivalent to previous iterations
Synchronizing custom agent behaviors and prompts across different IDE environments

关于

主要功能

Multi-agent skill dispersal protocol (Claude, Codex, Cursor)
2 GitHub stars
Observational bridge types for version-aware synchronization
Self-rewriting capabilities via MCP Tasks integration
Automated bisimulation verification and conflict resolution
GF(3) ternary logic conservation for state transitions

使用场景

Automating the discovery and propagation of new skills from web resources to local agent directories
Verifying that updated agent versions remain functionally equivalent to previous iterations
Synchronizing custom agent behaviors and prompts across different IDE environments