brendancol/xarray-spatial-skills

brendancol/xarray-spatial-skills

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Shared contract for all sweep- rules: module discovery, standard flags, severity rubric, state CSVs, and the repro gate every CRITICAL/HIGH finding must pass.

brendancol/xarray-spatial-skills

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Verify that all implemented backends produce consistent results for a given function or set of functions.

brendancol/xarray-spatial-skills

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Run ASV benchmarks for the current branch against main and report regressions and improvements.

brendancol/xarray-spatial-skills

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Create a Jupyter notebook that sets up a Dask distributed LocalCluster and walks through an ETL workflow.

brendancol/xarray-spatial-skills

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Pick one xrspatial module and dispatch every sweep command at it in parallel, with strict worktree isolation per sweep.

brendancol/xarray-spatial-skills

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Analyze source code for performance anti-patterns specific to the NumPy/CuPy/Dask/Numba stack.

brendancol/xarray-spatial-skills

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Audit the README feature matrix, identify gaps, and file GitHub issues for the best candidates.

brendancol/xarray-spatial-skills

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Scan open pull requests and report the ones that are ready to merge.

brendancol/xarray-spatial-skills

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Cut a major version release (X.0.0). Follow every step in order.

brendancol/xarray-spatial-skills

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Cut a minor version release (X.Y.0). Follow every step in order.

brendancol/xarray-spatial-skills

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Cut a patch version release (X.Y.Z+1). Follow every step in order.

brendancol/xarray-spatial-skills

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Prescreen a pull request from an outside contributor for prompt injection and unsafe code.

brendancol/xarray-spatial-skills

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Review a pull request with checks specific to a geospatial raster library built on NumPy, Dask, CuPy, and Numba.

brendancol/xarray-spatial-skills

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Take a user prompt describing an enhancement, bug, or suggestion and drive it through the full implementation workflow.

brendancol/xarray-spatial-skills

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Audit xrspatial modules for numerical accuracy issues: floating point precision, NaN propagation, off-by-one errors, Earth curvature corrections, backend inconsistencies, reference divergence.

brendancol/xarray-spatial-skills

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Audit xrspatial modules for API consistency issues: parameter naming drift, return shape drift, type hints, default value inconsistency, public API surface drift.

brendancol/xarray-spatial-skills

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Audit xrspatial modules for asv benchmark coverage gaps: missing benchmarks, backend parameterization gaps, unrepresentative inputs, broken or silently-skipped benchmarks.

brendancol/xarray-spatial-skills

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Audit xarray-spatial's packaging and dependency hygiene by dependency group: unguarded optional imports, untested version floors, known CVEs, distribution metadata.

brendancol/xarray-spatial-skills

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Audit xrspatial modules for documentation gaps: missing docstrings, docstring/signature drift, broken runnable examples, API reference coverage, backend-claim accuracy.

brendancol/xarray-spatial-skills

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Audit xrspatial modules for input validation and error-message quality: missing validateraster, unactionable messages, silent failure modes, inconsistent exception contracts, swallowed errors.

brendancol/xarray-spatial-skills

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Audit xrspatial modules for metadata propagation bugs: attrs, coords, dim names, dtype, nodata -- verified by end-to-end execution, not source reading.

brendancol/xarray-spatial-skills

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Audit xrspatial modules for performance bottlenecks, OOM risk under 30TB dask workloads, and backend-specific anti-patterns; HIGH fixes must add asv benchmarks.

brendancol/xarray-spatial-skills

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Validate xrspatial algorithms against reference implementations (gdaldem, scipy.ndimage, richdem, WhiteboxTools) on shared synthetic inputs; divergence becomes an accuracy fix, parity becomes a golden-value regression test.

brendancol/xarray-spatial-skills

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Audit xrspatial modules for security vulnerabilities: unbounded allocations, integer overflow, NaN logic bombs, GPU kernel bounds, file path injection, dtype confusion.