Prime-TB Cut Mother Operator: A Meta-Operator for Decomposing Composite AI Outputs and Constructing Executable Output Standards for AI/XAI

Prime-TB Cut Mother Operator: A Meta-Operator for Decomposing Composite AI Outputs and Constructing Executable Output Standards for AI/XAI Author: Phan Thành Trung Affiliation: Independent Researcher, Vietnam ORCID: 0009-0000-7520-6781 Abstract The rapid development of artificial intelligence has made AI outputs increasingly fluent, persuasive, and functionally useful. However, the standard for determining whether an AI output is “good,” “correct,” “usable,” or “trustworthy” remains structurally underdefined. Most current evaluations rely on user perception, task-based benchmarks, or isolated performance metrics, while the output itself is often a composite object consisting of multiple layers: factual content, reasoning structure, task alignment, contextual fit, explanatory trace, uncertainty, safety boundary, actionability, and style. This whitepaper proposes the Prime-TB Cut Mother Op