Effective capacity-loss diagnosis and life-time prediction are the foundations of battery second-use technology and will play an important role in the development of the new energy industry. Of the two, the capacity-loss diagnostic, as a precondition of the life-time prediction, needs to be studied first. Performing a capacity-loss diagnosis for an aging cell consists of finding the decisive degradation mechanisms for the cell's capacity degradation. Because a cell's capacity just equals the span of the open-circuit voltage (OCV), when suspect degradation mechanisms affect a cell's capacity, they will leave corresponding and particular clues in the OCV curve. Taking a cell's OCV as the diagnostic indicator, a multi-mechanistic and non-destructive diagnostic method is developed in this paper. To establish an unambiguous relationship between OCV changes and the combinations of the decisive mechanisms, all the possible OCV changes under various aging situations are systematically analyzed based on a novel simultaneous coordinate system, in which the effects of each suspect capacity-loss mechanism on the OCV curve can be clearly represented. As a summary of the analysis results, a straightforward diagnostic flowchart is presented. By following the flowchart, an aging cell can be diagnosed within three steps by observation of the OCV changes.