Ancient manuscripts are the primary source of ancient linguistic corpora. However, some of them exhibit duplications due to unintentional repeated publication or deliberate forgery. Notable examples include counterfeit fragments within the Dead Sea Scrolls and the repeated publication of Oracle Bones (OB). Identifying such duplicates is critical for both archaeological curation and historical research. We present OBD-Finder, an explainable coarse-to-fine framework for large-scale duplicate discovery in ancient manuscript collections, with a primary focus on Oracle Bones. OBD-Finder integrates unsupervised low-level keypoint matching with high-level character-centric content similarity to progressively filter and rank duplicate candidates, balancing retrieval accuracy with computational efficiency. Designed as a practical, transparent, and domain-expert-friendly tool, the system produces candidate duplicates and supports expert inspection and validation. In real-world deployment, OBD-Finder has enabled domain experts to uncover 63 previously unknown duplicate Oracle Bone pairs that had remained overlooked for decades. Extensive experiments also confirm that OBD-Finder achieves competitive retrieval accuracy while offering substantially superior efficiency and interpretability compared to existing approaches. Code and deployed system are publicly available: https://github.com/cszhangLMU/OBD-Finder/.