High-fidelity thermo-fluid simulations of Laser Powder Bed Fusion (LPBF) generate detailed three-dimensional fields describing melt-pool evolution, porosity formation, and track stability. In practice, however, melt-pool characterisation is often reduced to a small number of centreline-based geometric measurements, which neglect along-track spatial variability and hinder reproducible and systematic analysis. This contribution presents a reproducible computational methodology for full-field melt-pool characterisation in LPBF single-track simulations. The approach reconstructs cross-sections along the scan direction directly from simulation fields, verifies melt-track continuity, and computes spatially resolved melt-pool width, depth, height, and porosity. Porosity is quantified from the as-solidified track using volume-of-fluid information, enabling section-wise assessment of defect prevalence alongside geometric descriptors. In contrast to pointwise or centreline-only metrics, the proposed methodology yields continuous fields of geometric and porosity measures along the entire track, together with well-defined aggregate statistics. The methodology is solver-agnostic and is demonstrated using a parameter sweep of high-fidelity LPBF simulations performed with an OpenFOAM-based thermo-fluid solver configured according to a validated benchmark case. The results reveal pronounced along-track variability in all geometric quantities and in porosity, highlighting behaviour that is not captured by conventional centreline measurements and that is directly linked to melt-pool stability. By providing consistent full-field metrics in a structured format, the proposed approach supports systematic parameter studies and enables downstream analyses, including surrogate modelling. Overall, the methodology establishes a robust and extensible foundation for reproducible melt-pool analysis in computational LPBF research.