We develop a data-driven framework to systematically test the dragon-king earthquake hypothesis. Our method combines objective spatial clustering, based on data-adaptive kernel density estimation, with a high-power sequential outlier detection technique. We apply this framework to seismicity surrounding the 1975 Haicheng mL 7.4 and 1976 Tangshan mL 7.9 earthquakes. For Haicheng, the mainshock shows a strong dragon-king signature in its pre-mainshock sequence, with p-values between 0.03 and 0.07 across a stable range of density thresholds used to define natural seismicity clusters. Post-mainshock and combined sequences yield slightly higher p-values (up to 0.09). In contrast, Tangshan's mainshock exhibits a weaker outlier signal before the event (p-values in the range 0.05-0.15) but a stronger dragon-king signature afterward, with p-values from 0.015 to 0.05. The evidence that the Haicheng and Tangshan mainshocks exhibit dragon-king characteristics supports the idea that some large and great earthquakes arise from a maturation process that may enhance predictability.