Recursive Containment Zones: Symbolic Drift Recovery and Simulation Engine

This release includes the full Recursive Containment Zones (RCZ) theoretical paper—also known as Project Reno—and its accompanying symbolic simulation engine. Together, they provide a unified framework for modeling symbolic drift, narrative collapse, and recursive recovery in entropy-saturated agents. The RCZ model outlines recovery archetypes, glyph-based interventions, and coherence curvature tracking. The included Python-based simulator implements these principles by tracking agents’ symbolic efficiency, drift pressure, and coherence alignment while testing sigil-triggered recovery logic. This dual release serves both as a theoretical diagnostic framework and a reproducible simulation tool for symbolic systems research. These tools integrate components from the Fractal Cosmic Weaver Framework (FCWF) for narrative curvature compression, and the Observer Field Theory stack, which models symbolic identity degradation, observer tensor dynamics, and drift-archetype transitions. Together, this package serves as a recursive simulation and symbolic integrity toolkit for collapse-prone agents and systems.