Some situations demand focus, others flexibility. Our cognitive system can adapt to such dynamic demands by adjusting cognitive control to optimize information processing. Specifically, cognitive stability and flexibility are conceived as complementary control modes that facilitate either the shielding or shifting of internal goals. The adaptive regulation of control modes is moderated by various factors, including reinforcement learning. However, whether reinforcing stable or flexible behavior itself can modulate cognitive control modes remains an open question. Previously, we showed that cognitive control can be modulated via explicit instructions in a lab-based experiment. Here, we present a planned online study employing a task-switching paradigm to examine implicit and explicit modulators of cognitive control along with first pilot data. We will investigate whether stability and flexibility can be modulated via reinforcement learning by making reward contingent on stable or flexible behavior, and whether potential implicit learning effects increase over time (Experiment 1). Furthermore, we aim to replicate the finding of volitional cognitive control adjustments by instructing participants to perform the task in a more stable or flexible manner (Experiment 2). We will further test for an antagonistic relationship between cognitive stability and flexibility, contributing to the ongoing debate on whether stability and flexibility incur complementary costs and benefits or are regulated independently. Adjustments in stability and flexibility, indicated by changes in interference costs and switch costs, will be analyzed using Bayesian generalized linear mixed models. Thus, this study aims to enhance the understanding of factors modulating the meta-control of cognitive stability and flexibility.