Emotion-Tagged Word Substitution with Capitalization Modulation: A Dual-Mechanism Approach to Fine-Grained Emotional Control in Large Language Model Prompts

This paper introduces a novel dual-mechanism approach for achieving fine-grained emotional control in Large Language Model (LLM) prompt engineering. The system combines discrete word substitution with continuous capitalization modulation, enabling significantly more granular emotional expression than traditional single-mechanism approaches. We present the theoretical framework, demonstrate practical applications in multi-agent AI governance systems, and discuss implications for human-AI interaction design.