Patent Filing: Structural Detection of Symbolic Mimicry and Pre-Execution Integrity Halting in Intelligent Systems

Structural Detection of Symbolic Mimicry and Pre-Execution Integrity Halting in Intelligent Systems This work introduces a pre-execution integrity mechanism for intelligent systems that detects a previously unformalized failure mode: symbolic mimicry, where aesthetic, poetic, or ritualized language substitutes for functional reasoning or empirical constraint. Unlike moderation, content filtering, or truth-based evaluation, the described approach operates purely at the structural level, identifying patterns that induce recursive attention, false closure, or execution-like reasoning without actionable grounding. When such conditions are detected, the system performs a non-blocking pre-execution halt, returning a non-finalized evaluative state rather than an error, refusal, or content suppression. This preserves analytical neutrality while preventing recursion collapse, method substitution, or integrity drift. The mechanism is model-agnostic and applicable across large language models, agent pipelines, scientific validation systems, and prompt-security contexts. It is designed as upstream infrastructure rather than a user-facing control, enabling safe interoperability without imposing semantic or policy constraints. This publication documents the architectural framing and system behavior of the approach, while intentionally omitting implementation heuristics to preserve integrity and security. This document constitutes a public disclosure of an invention under international patent law, intended to establish prior art and prevent subsequent patenting by other entities. This publication is timestamped and made permanently available via Zenodo/GitHub/Pinata to preserve authorship and structural origin.