The ability to proactively offer assistance promises to make personal agents more helpful to their users. We characterize the properties desired of proactive behaviour by a personal assistant agent in the realm of task management, and present an extended agent cognition model that features a meta-level layer charged with identifying potentially helpful actions and determining when it is appropriate to perform them. The reasoning that answers these questions draws on a theory of proactivity that describes user desires and a model of helpfulness. Operationally, assistance patterns represent a compiled form of this knowledge, instantiating meta-cognition over the agent’s beliefs about its user’s activities as well as over world state. We have implemented the resulting generic framework for proactive goal generation and deliberation as part of a personal assistant agent in the desktop domain.