Data Grid is one of key technologies to build up large-scale dataset storage system by connecting scattered storage resources dispersedly located in the Grid. One major challenge in data grids is how to provide good and timely access to huge amount of data in distributed locations, given the high latency of interconnection networks. Parallel downloading methods can improve download efficiency and performance, and for such, processes should have started from appropriate locations. In this research paper, we present the design framework of PU-DG Optimizer toolbox (also known as PU-DG Optibox) for data grid environments. The proposed toolbox is a package containing a number of high-end techniques and algorithms running as middleware on top of data grid platforms, in order to optimize file downloads, by improving its efficiency and performance. Moreover, PU-DG Optibox not only provides users and developers possibilities for setting their own priority strategies, as also different downloading modes. Furthermore, workload balancing to avoid low quality computing node to execute highly complex job is also included in this design. Experimental results of techniques packaged in the proposed toolbox demonstrate its potential and effectiveness.