Task execution by a coordinated team of robots that feature different skills and competencies, offers certain advantages over a single robot. To better coordinate individual actions, effective planners are necessary to consider the time that agents devote to the completion of partial activities, the different skills that agents may have and the qualitative differences in action implementation by different agents. Multi-agent collaboration in everyday environments assumes the coordination of individual activities in the presence of external disturbances. In this context, incremental approaches seem more appropriate for planning multi-agent collaboration offering increased flexibility against dynamic changes. We propose a new time-informed planning framework for incrementally guiding a team of heterogeneous robots. The proposed approach, takes into account the skills and limitations of individual agents in order to assign them tasks which improve their usability for the team and facilitate the accomplishment of the common goals.