That does not work as advertised.

If you leave an agent for hours trying to increase coverage by percentage without further guiding instructions you will end up with lots of garbage.

In order to achieve this, you need several distinct loops. One that creates tests (there will be garbage), one that consolidates redundant tests, one that parametrizes repetitive tests, and so on.

Agents create redundant tests for all sorts of reasons. Maybe they're trying a hard to reach line and leave several attempts behind. Or maybe they "get creative" and try to guess what is uncovered instead of actually following the coverage report, etc.

Less capable models are actually better at doing this. They're faster, don't "get creative" with weird ideas mid-task and cost less. Just make them work one test at the time. Spawn, do one test that verifiably increases overall coverage, exit. Once you reach a treshold, start the consolidating loop: pick a redundant pair of tests, consolidate, exit. And so on...

Of course, you can use a powerful model and babysit it as well. A few disambiguating questions and interruptions will guide them well. If you want true unattended though, it's damn hard to get stable results.