MetEva is a Python library for meteorological forecast verification, developed by the China Meteorological Administration (NMC/CMA). It provides a comprehensive suite of tools for reading, processing, and verifying weather forecasts against observations. The library supports both station (point) and gridded data, with I/O for multiple formats including MICAPS, GRIB, NetCDF, GDS, and CMADaaS. Verification methods cover continuous (ME, MAE, RMSE, correlation), categorical (TS, ETS, POD, FAR), probability (Brier, ROC), ensemble (CRPS, spread-skill), and spatial (FSS, MODE, CRA, SAL, fuzzy logic) scores. It also includes operational product generation for time-series plots, spatial maps, and regulatory scoring. The codebase is large and feature-rich, but exhibits code duplication, hardcoded paths, and mixed Chinese/English comments, indicating an evolving codebase with some technical debt.