  Requirements often specify the expected system behavior by using causal
relations (e.g., If A, then B). Automatically extracting these relations
supports, among others, two prominent RE use cases: automatic test case
derivation and dependency detection between requirements. However, existing
tools fail to extract causality from natural language with reasonable
performance. In this paper, we present our tool CiRA (Causality detection in
Requirements Artifacts), which represents a first step towards automatic
causality extraction from requirements. We evaluate CiRA on a publicly
available data set of 61 acceptance criteria (causal: 32; non-causal: 29)
describing the functionality of the German Corona-Warn-App. We achieve a macro
F_1 score of 83%, which corroborates the feasibility of our approach.
