In this paper we analyze the vocabulary of an action description language to be used, together with a low level object controller, by a humanoid robot in two specific scenarios: a kitchen and a collaborative workshop table. A methodology to acquire this knowledge is presented and then it is applied to these two scenarios. The collected data allows to establish a priority of which actions needs to be implemented with robot controllers, which objects need to be manipulated and how much variation they exhibit between different scenarios or different complex tasks.