<tt>SynKit</tt> : A Graph-Based Python Framework for Rule-Based Reaction Modeling and Analysis

Computational modeling of chemical reactions is fundamental to modern synthetic chemistry but is often hindered by a fragmented software ecosystem and the complexity of accurately representing the reaction mechanisms. To address this, we introduce SynKit, an open-source Python library that provides a unified, chemically intuitive framework for reaction informatics. SynKit performs core tasks such as reaction canonicalization and transformation classification, while other functionalities─such as synthetic route construction through rule composition─are supported through integration with external libraries. The newly introduced <i>Mechanistic Transition Graph</i> extends the traditional net-change representation of the <i>Imaginary Transition State</i> by explicitly modeling the sequence of bond-forming and bond-breaking events, capturing transient intermediates, and providing deeper mechanistic insight. Designed for easy installation and broad compatibility, SynKit integrates smoothly into existing computational workflows for exploring complex <i>Chemical Reaction Networks</i>. For more advanced network analyses, it interfaces with specialized tools (e.g., MØD) to support exhaustive mechanism enumeration and kinetics-aware studies. By combining advanced mechanistic modeling with an accessible, modular design, SynKit supports more reproducible and rigorous research in automated synthesis planning.