What problem does it solve? Xarray code often fails silently through coordinate misalignment, accidental data materialization, or incorrect weighted reductions. This Skill enforces explicit execution contracts for DataArray and Dataset workflows so alignment, indexing, reduction, and I/O behavior stay correct and verifiable. ## Core Features & Use Cases - Alignment and indexing contracts: Declare exact, inner, outer, left, or right join policy and choose between label-based .sel and position-based .isel selection before combining arrays. - Evaluated recipes with tests: Apply verified anchors for exact-aligned arithmetic, mask-aware weighted means, and daily time resampling, each paired with a pytest verification contract. - Lazy execution and I/O boundaries: Preserve Dask-backed laziness across chunked data and state NetCDF/Zarr round-trip requirements at storage boundaries. - Use Case: When computing a weighted time mean over observations with missing values, use the mask-aware weighted reduction recipe to normalize weights only over valid samples and reject zero effective weight with a precise error. ## Quick Start Ask the assistant to write or review an Xarray function that computes a weighted time mean with explicit alignment and missing-data handling, including its pytest verification.
