Through structural analysis of LLM generated or LLM refined whitepapers, this study identifies a recurring pattern in tokenized finance: legitimacy is simulated through formal syntactic depth rather than verifiable disclosure. It introduces the Syntactic Deception Risk Index (SDRI), a quantitative measure of non referential persuasion derived from syntactic volatility. Grounded in Algorithmic Obedience and The Grammar of Objectivity, the findings show that high risk disclosures converge on a formal grammar that substitutes substantive content with surface coherence. The concept of sovereign syntax is formalized as the regla compilada (type 0 production) that governs trust independently of source or reference. From this model follow concrete pathways for audit automation, exchange side filtration, and real time regulatory screening. SDRI thus exposes how non human authority embeds in financial language without a traceable epistemic anchor. DOI: https://doi.org/10.5281/zenodo.16421548 This work is also published with DOI reference in Figshare https://doi.org/10.6084/m9.figshare.29646473 and Pending SSRN ID to be assigned. ETA: Q3 2025.