Skill UI

Automatically activates when chart type recommender needs arise, guiding data analysts through SQL, visualization, statistics, and BI patterns to deliver production-ready recommendations.

Automates the data story outlining process for analytic workflows, offering guidance on SQL, visualization, statistics, and BI so teams can structure insights consistently.

Automates guidance for date range analytics, covering SQL, visualization, statistics, and BI, with code generation and validation to support data analytics workflows.

Automated assistant for forecast generator tasks in data analytics, guiding through SQL, visualization, statistics, and BI workflows with best practices, ready-to-run code, and validation.

Automates funnel analysis builder workflows by offering guidance on SQL, visualization, statistics, and BI best practices for data analytics teams needing production-ready insights.

Automates report template creation within data analytics by guiding SQL, visualization, statistics, and BI best practices, generating ready-to-use configurations and validating outputs.

Query the NHGRI-EBI GWAS Catalog for SNP-trait associations, fetch study metadata, variant and trait details, and download summary statistics via the web or REST APIs to support genetic epidemiology and polygenic risk modeling.

Structured manuscript and grant review guidance that walks reviewers through methodology, statistics, reporting compliance, and constructive feedback for rigorous scientific evaluation across disciplines.

PyDESeq2 brings the DESeq2 differential expression workflow to Python, letting users load bulk RNA-seq counts, specify design formulas, fit DESeq2 models, run Wald tests with FDR correction, optionally apply apeGLM shrinkage, and export gene-level statistics within pandas/AnnData pipelines.

Statsmodels is a comprehensive Python library dedicated to advanced statistical modeling and econometrics. It provides tools for rigorous statistical inference, including Ordinary Least Squares (OLS), Generalized Linear Models (GLM), mixed-effects models, and time series analysis (ARIMA). Use this skill for detailed diagnostics, coefficient estimation, hypothesis testing, and producing publication-ready statistical reports in fields like econometrics and biostatistics.

Provides open REST access to the U.S. Treasury Fiscal Data API so analysts can pull national debt, spending, revenue, interest rates, exchange rates, auctions, and savings bond statistics without an API key; useful for financial dashboards, debt tracking, and research involving federal fiscal metrics.

Vaex is a high-performance Python library for lazy out-of-core DataFrames that process billions of rows without RAM. Use it to analyze massive CSV/HDF5/Arrow/Parquet tables, compute fast statistics, visualize big data, and build scikit-learn pipelines.