CoSQ Framework Lets AI Agents Self-Assess Before Answering to Reduce Hallucinations

Chain-of-Self-Questioning (CoSQ) is a prompt-only framework designed to help AI agents decide when to withhold an answer rather than produce a confident but incorrect response. It works by prompting the agent to evaluate whether it has sufficient information before committing to a reply, requiring no model retraining or external verification tools. The framework offers three variants — Grounded, Critical, and Adaptive — each balancing abstention risk against answer coverage differently. A configurable confidence threshold controls how cautious the agent is, with higher thresholds yielding fewer but more accurate responses. CoSQ is designed to integrate into existing agent pipelines without altering the underlying model or orchestration infrastructure.