Learning shared structures across changing environments enables an agent to efficiently retain obtained knowledge and transfer it between environments. A skill is a promising concept to represent shared structures. Several recent works proposed unsupervised skill discovery algorithms that can discover useful skills without a reward function. However, they focused on discovering skills in stationary environments or assumed that a skill being trained is fixed within an episode, which is insufficie…