We introduce a new method for vertex clustering or community detection on directed graphs (digraphs). The new method is an extension of the BlueRed method introduced initially for undirected graphs. Complementary to supervised or semisupervised classification, unsupervised graph clustering is indispensable to exploratory data analysis and knowledge discovery. Conventional graph clustering methods are fundamentally hindered in effectiveness and efficiency by either the resolution limit or various problems with resolution parameter selection. BlueRed is originative in analysis, modeling, and solution approach. Its clustering process is simple, fully autonomous and unsupervised. Among other potential impacts, BlueRed breaks new ground for high-throughput, low-cost and high-performance graph clustering computation, as it has removed the barrier of parameter tuning/selection.