A Methodological Framework for Training Tool-Aware AI Entertainers for Live Streaming

This paper introduces a methodological framework for training AI systems to function as tool-aware entertainers in live streaming environments. Moving beyond generic language models that generate scripted responses, the framework conceptualizes tool awareness as a triadic competence: the ability to perceive available digital tools---such as real-time graphics engines, audience sentiment analyzers, and interactive overlay systems; to select among them dynamically based on both performative goals and unfolding audience conditions; and to orchestrate their use within the strict latency and coherence constraints of live, multimodal performance. Grounded in an interdisciplinary synthesis of performance theory, cognitive science, and machine learning, the proposed architecture comprises three interdependent layers: a Tool Perception Layer that embeds tool capabilities from documentation and interface signals; a Performative Intent Mapping Layer trained on annotated live-stream data to link social intentions---like building rapport or escalating excitement---to appropriate tool combinations; and a Runtime Orchestration Layer that schedules tool invocations with built-in fallback logic and timing safeguards. The framework is supported by a curated, multimodal training corpus drawn from diverse streaming genres and regions, and evaluated through a dual-axis protocol assessing both functional reliability and performative appropriateness. Implementation considerations address platform-specific constraints, cultural calibration for regional norms---particularly in East Asian streaming ecologies---and ethical integration of human oversight as a structural component of the training loop. The work does not deliver a deployed system but advances a domain-specific scaffolding for engineering AI performers whose actions are intentional, contextually grounded, and aesthetically coherent. It positions tool awareness not as technical utility but as a form of performative cognition essential to meaningful human--AI co-presence in real-time digital culture.