Whitepaper about Plugin Based Proactive Multimodal Interaction Trigger Architecture

LLM-driven agents have achieved remarkable progress in passive response, yet they remain fundamentally limited by user-initiated interaction paradigms—unable to proactively perceive environmental changes or anticipate user needs. This paper addresses the architectural bottlenecks that prevent proactive interaction: trigger logic tightly coupled with the kernel, absence of proactive triggering mechanisms, and lack of scalable plugin ecosystems. We propose a Plugin-Based Proactive Multimodal Interaction Trigger Architecture that decouples trigger logic from the scheduling kernel through a standardized three-file plugin format (`trigger`, `trigger_mode.cfg`, `ACTIVE.md`), enabling hot-swappable plugins with zero kernel modification. A dual-mode scheduling mechanism (periodic for continuous monitoring, idle for user-absence detection, with idle_once as a single-trigger variant) achieves graded, low-disturbance interaction while the Triple Dilemma constrains architectural trade-offs. The architecture has been implemented in the Prosophor project—a C++ intelligent coding assistant CLI—demonstrating engineering feasibility. Post-trigger LLM linkage generates scenario-aware responses across three modes: proactive dialogue, task execution with notification, and silent background execution. This paper contributes the first engineering framework for proactive agent interaction, bridging the gap between passive response systems and autonomous AI.