Client-Side Human-in-the-Loop (HITL) Mechanisms for Latency-Free DOM Selector Repair in Robotic Process Automation

This paper describes a method for locally repairing broken web automation scripts (RPA) in real-time. Unlike cloud-based self-healing systems that rely on server-side DOM analysis (introducing latency and privacy risks) or Logic Confirmation systems (e.g., Amazon Bedrock) that only validate intent, this architecture utilizes a local 'Asrafo Kernel.' This mechanism couples probabilistic semantic discovery (via vector embeddings) with a deterministic 'Teacher Mode' to resolve operational drift. By persisting repair logic as semantic signatures rather than rigid object repositories, the system achieves immediate self-healing without data exfiltration or code recompilation.