LARQL treats neural network weights as a graph database to enable complex queries of model internals. This tool allows developers to extract specific structural patterns from weights without manual tensor slicing. It simplifies the analysis of model architecture. Practitioners can now audit internal representations using a familiar query language instead of raw Python scripts.