In September 2026, a South Korean research institution released the KOPA-Bench benchmark, which included 145 real-world tasks aimed at evaluating the performance of open-source models in multi-step tool calls across government APIs. To address the lack of existing evaluation criteria and the performance gap between models, the team proposed the EDGE method based on data synthesis from execution dynamic graphs. This method constructs a graph of tool input-output relationships and filters out successful call chains to generate executable complex trajectory data. The 9B-parameter model, fine-tuned using GRPO, performed significantly better than the unfine-tuned 27B model of the same family in both KOPA-Bench and BFCL benchmarks, achieving performance close to optimal levels.