In response to the issue that existing cycle slip detection methods lack systematic performance evaluation tools, this paper proposes a comprehensive evaluation approach that considers all epochs. By uniformly introducing cycle slips across all epochs, the method comprehensively reflects the true performance of different cycle slip detection algorithms over the entire observation period. Starting from three dimensions: combined noise, test statistic detection performance, and cycle slip detection results, three performance indicators are constructed: the root mean square error (RMSE) of the test statistic, the ratio of test statistic variation to RMSE, and the missed detection probability over all epochs. These indicators are used to systematically evaluate the performance differences of five cycle slip detection algorithms: Melbourne-Wübbena (MW), sliding window improved MW, triple-frequency pseudorange and phase, triple-frequency geometry-free (GF), and triple-frequency second-order time-difference phase ionospheric residual (STPIR). The results show that for all cycle slips within two weeks of the B1C/B2a/B3I signals, the triple-frequency GF cycle slip detection algorithm with a combination coefficient of (1, 2, -3) performs the best. Its test statistic RMSE is 0.006 2, the ratio of test statistic variation to RMSE is 100.56, and the missed detection probability over all epochs is only 7.28%. This performance evaluation method provides an objective quantitative basis for comparing the performance of cycle slip detection algorithms.