Pau Febrer delivered three targeted enhancements across the metatensor/metatrain, lab-cosmo/atomistic-cookbook, and metatensor/metatensor repositories, focusing on performance, CI/CD reliability, and flexible data validation. He introduced field-level data loading in Python for DiskDataset, reducing memory and I/O overhead by allowing selective field access. In lab-cosmo/atomistic-cookbook, he improved GitHub Actions workflows by enabling authenticated artifact downloads for forked pull requests using YAML-based CI configuration. For metatensor/metatensor, he added an option to skip gradient metadata checks in tensor comparisons, streamlining large model workflows. His work demonstrated depth in API design, dataset management, and robust integration of CI/CD practices.