Development and validation of a multi-agent AI pipeline for automated credibility assessment of tobacco misinformation: a proof-of-concept study

Our proof-of-concept agentic AI pipeline demonstrates substantial agreement with expert assessments of tobacco-related claims while providing dramatic speed improvements. By combining zero-shot LLM reasoning, retrieval-grounded evidence verification, and a transparent five-level scoring schema, the system offers a practical tool for real-time misinformation monitoring in public health. This proof-of-concept establishes technical feasibility for automated tobacco misinformation assessment, with validation results supporting further development and larger-scale testing before operational deployment.