The pymatgen-analysis-defects package is a Python tool for analyzing point defects in crystalline materials. It is designed to be easily integrated into high-throughput workflows to manage complex defect calculations. However, it focuses on defect analysis rather than high-throughput workflow automation, making it a standalone analysis package. The package provides a base library for analyzing point defects without relying on any specific high-throughput workflow framework. It also includes tools for analyzing carrier recombination in defects, such as calculating the chemical potential contribution to defect formation energy, the Freysoldt finite-size correction, optical transitions between states, and non-radiative recombination. A core feature of the package is its ability to automatically define point defects. While symmetry analysis on the atomic structure is usually sufficient for substitutional and vacancy defects, the electronic charge density is most effective for placing interstitial defects at symmetry-inequivalent positions. The package also includes a structure-only definition of point defects to aggregate results from multiple calculations of the same defect, enabling the creation of a persistent database of point defects. The package is integrated with the atomate2 workflow framework to provide a complete set of tools for simulating, analyzing, and managing point defect calculations. It includes a basic example of integration with the atomate2 workflow framework, which generates a Flow object containing instructions to dynamically create all required defect calculations. The package contains contributions from other open-source projects, including the finite size correction from pyCDT and the non-radiative recombination code from nonrad. The work was performed under the auspices of the U.S. DOE by Lawrence Livermore National Laboratory.The pymatgen-analysis-defects package is a Python tool for analyzing point defects in crystalline materials. It is designed to be easily integrated into high-throughput workflows to manage complex defect calculations. However, it focuses on defect analysis rather than high-throughput workflow automation, making it a standalone analysis package. The package provides a base library for analyzing point defects without relying on any specific high-throughput workflow framework. It also includes tools for analyzing carrier recombination in defects, such as calculating the chemical potential contribution to defect formation energy, the Freysoldt finite-size correction, optical transitions between states, and non-radiative recombination. A core feature of the package is its ability to automatically define point defects. While symmetry analysis on the atomic structure is usually sufficient for substitutional and vacancy defects, the electronic charge density is most effective for placing interstitial defects at symmetry-inequivalent positions. The package also includes a structure-only definition of point defects to aggregate results from multiple calculations of the same defect, enabling the creation of a persistent database of point defects. The package is integrated with the atomate2 workflow framework to provide a complete set of tools for simulating, analyzing, and managing point defect calculations. It includes a basic example of integration with the atomate2 workflow framework, which generates a Flow object containing instructions to dynamically create all required defect calculations. The package contains contributions from other open-source projects, including the finite size correction from pyCDT and the non-radiative recombination code from nonrad. The work was performed under the auspices of the U.S. DOE by Lawrence Livermore National Laboratory.