Advances in the development of devices with handwritten input, and the emergence of deep learning have led to the rapid development of handwriting recognition applications, but the methods and implications of handwritten interaction on the Lock Screen of the smartphone, taking into account usability, are still not sufficiently considered in existing studies. In this paper, we propose a novel method for the quick processing of handwritten input and delivering results without explicitly starting the presumed application associated with an action. Handwritten input is processed either with or without requiring authorization, depending on the sensitivity of the implied action. The method comprises the initial handwritten input processing to locate and extract textual information, then entity extraction from the recognized text, and device context identification. The extracted entities and the current device context are analyzed to identify the action imposed by the user, to process the input, and to obtain and deliver the results in a single or a few steps. The proposed method is suitable for integration with the first screen of the device, also known as the Lock Screen, but it can also be utilized in applications based on handwriting input. The user study demonstrates that the proposed method accelerates the time to completion (TTC) of the most common actions by 20% compared to traditional input when all the necessary steps are required to be explicitly performed by the user.