For all the positions of a game, the evaluation of the engine does not have the same precision.
The same goes for experience data, sometimes there are many, sometimes there are few.
Sometimes they are reinforced with refined scores at very great depths.
So with values fixed for all the positions of a game like those of the "Experience Book Min Depth / Eval Importance" options, it is not optimal.
Engine's moves are not always in conformity with its experience data.
D.C.S has been designed to make the best use of experience data in each position.
As i don't read the C/C++ language and i don't know anyone who can modify the source codes of the private engines,
i coded a tool which drives several engines simultaneous, which chooses the most efficient moves or the moves of the reinforced data or the moves from the opening book.
The move's choice depends on the position of the game, the among/quality of experience data, what contains the opening book, etc.
D.C.S passes UCI commands regarding opening book options to the "book_engine" configured to choose moves from the opening book.
D.C.S passes other UCI commands regarding engines settings to the "playing_engine" configured to analyze the positions, choose moves from the experience file, save new moves and update the experience data, etc.
D.C.S needs an INI file which looks like this :

Throughout this "proof-of-concept" phase, i used Eman 8.40 as playing_engine, asmFish 291118 as book_engine and Depth4_180423.exp as the experience file.
The rest of the D.C.S. features/details remains under NDA...