This paper proposes Dependency-Aware Reward Shaping (DARS), a method for assigning step-level credit to reinforcement learning tasks. DARS represents task progress as a dependency graph and assigns rewards based on the graph distance from broken prerequisites. The method integrates with existing agentic training methods and improves success rates in various tasks.