The idea behind it is to use cargo-mutants to generate mutants, and then solve the set cover problem for those mutants to suggest which tests can be eliminated. (use a greedy algorithm to cover the detected mutants with fewer tests)
I came up with this as a countermeasure against the monotonically increasing tests that tend to accumulate, especially when coding with AI.
In fact, this very repository was also written using AI.
I ran this tool on a previous revision of this repository. There were 11 tests and 108 generated mutants: 73 were caught by the tests, 23 survived, and 12 failed to compile. I removed the 5 tests suggested by the tool and re-ran the same 108 mutants. The remaining 6 tests caught the exact same 73 mutants.
Tests partly serve as documentation, so simply applying this isn't necessarily recommended, but since writing less code still holds value in the AI era, I think this tool could be quite useful.