The ideal operational scenario for the future tokamak reactor is disruption-free operation. However, so far all the experimental evidence indicates that disruptions are unavoidable and can occur with alarming frequency when approaching reactor conditions (low q95, high radiated fraction, divertor detachment, etc). In this article, a unified strategy for disruption avoidance, prevention, and mitigation is proposed and validated on JET data. The approach is based on three phase-oriented predictors to detect the main instabilities leading to the undesired and sudden end of the discharge. The first model detects dangerous profiles as an early indication of a critical situation. The second is designed to identify multifaceted asymmetric radiation from the edge and other abnormal radiative events. The third model is devoted to mitigation, and triggers alarms around few tens of ms before the beginning of the current quench. The models have been trained and tested with a database of almost 1000 JET discharges of recent campaigns with the ITER-like wall. The overall performances are very close to 100% of successful detections with a few percent of false alarms. In addition to the first systematic use of visible cameras for disruption prevention in JET, the most relevant aspect of this work is related to the distribution of the alarms of the three predictors, which do not overlap and are sequential. Consequently, the three predictors are meant to work in parallel over running discharges and, depending on which one triggers the alarm, the cause can be determined and approximate remaining time to intervene can be estimated, potentially allowing for the optimisation of the remedial actions.