/xarray-for-multidimensional-data

Runs chunking benchmarks on Zarr datasets from local/S3/GCS paths or generates synthetic data, tests configurations across access patterns, and produces a performance report with recommendations.

Profiles datasets for structure, quality, distributions, and anomalies, outputting an EDA report from file paths or data source descriptions.

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ALWAYS invoke this skill when a user wants to perform computational analysis on data in this repository. This skill loads project-specific analysis conventions, dataset registries, and methodology requirements (validation checks, sensitivity sweeps, null hypothesis testing) that are not available from general knowledge — you cannot do the analysis correctly without consulting it first. Trigger for: running any named analysis technique (clustering, PCA, UMAP, differential expression, survival analysis, dose-response, model fitting, time-series, batch correction, statistical tests), exploring or investigating patterns in data, continuing or extending a previous analysis, debugging or troubleshooting analytical results (wrong clusters, unexpected patterns, parameter tuning). The user's intent must be to computationally process or model data — not just read it, not just look at a file. Do NOT trigger for: reading or previewing data files without analysis, writing reports or documents, brainstorming ideas, setting up or initializing repositories, installing conventions, ingesting or importing data files, fixing code bugs unrelated to analytical results, or updating documentation.

Adopts data-scientist persona to develop ML models, perform data analysis, and validate statistics based on the provided request.