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In the past few years, a successful line of research has led to lower bounds for several fundamental local graph problems in the distributed setting. These results were obtained via a technique called round elimination. On a high level, the round elimination technique can be seen as a recursive application of a function that takes as input a problem Π and outputs a problem Π' that is one round easier than Π. Applying this function recursively to concrete problems of interest can be highly nontrivial, which is one of the reasons that has made the technique difficult to approach. The contribution of our paper is threefold. Firstly, we develop a new and fully automatic method for finding so-called fixed point relaxations under round elimination. The detection of a non-0-round solvable fixed point relaxation of a problem Π immediately implies lower bounds of Ω(log_Δ n) and Ω(log_Δ log n) rounds for deterministic and randomized algorithms for Π, respectively. Secondly, we show that this automatic method is indeed useful, by obtaining lower bounds for defective coloring problems. More precisely, as an application of our procedure, we show that the problem of coloring the nodes of a graph with 3 colors and defect at most (Δ - 3)/2 requires Ω(log_Δ n) rounds for deterministic algorithms and Ω(log_Δ log n) rounds for randomized ones. Additionally, we provide a simplified proof for an existing defective coloring lower bound. We note that lower bounds for coloring problems are notoriously challenging to obtain, both in general, and via the round elimination technique. {Both the first and (indirectly) the second contribution build on our third contribution: a new method to compute the one-round easier problem Π' in the round elimination framework. This method heavily simplifies the usage of the round elimination technique, and in fact it has been successfully exploited in a recent work in order to prove quantum advantage in the distributed setting [STOC '25].}