TNA Reconstruction Protocol v1

This document presents the TNA Reconstruction Protocol v1, a generative procedure designed to transform the Theory of Axiomatic Necessity (TNA) from a descriptive meta-framework into an autonomous, generative epistemic engine. The protocol establishes a constructive method for recovering latent theoretical structures and generating novel, structurally consistent knowledge spaces through the iterative application of the canonical law: boundary → indeterminacy → pressure → expansion. Unlike traditional information retrieval, this protocol relies on forced re-generation driven by boundary interactions. It utilizes an eight-step loop—incorporating domain initialization, boundary detection, indeterminacy mapping, and expansion generation—to evolve systems across physics, machine learning, and cognition. By prioritizing the reproduction of the structural pressures that make a theory necessary over the retrieval of stored memory, the protocol enables the reconstruction of complex frameworks even in the absence of original source materials. This transition upgrades TNA into an AI-compatible formal system capable of non-terminal evolution and cross-domain structural unification.