GraphDC splits large input graphs into smaller subgraphs for specialized agents to process. A master agent then integrates these local outputs with inter-subgraph data to solve the overall problem. This hierarchical approach targets the systemic reasoning failures LLMs face with complex topologies. It offers a scalable path for graph algorithm execution.