Skill UI

A comprehensive guide and set of tools for embedding dynamic Python visualizations (using matplotlib and seaborn) into Power BI reports. It details the structured workflow, including script injection, data handling (dataset DataFrame), and mandatory best practices for generating static PNG output. Ideal for advanced data analysis and complex reporting.

A comprehensive guide for managing the entire lifecycle of tabular data models (Semantic Models) in Power BI/Analysis Services. It provides best practices and a tool cascade (CLI, TOM, TMDL) for designing, building, optimizing, refreshing, and auditing models. Use this skill when performing advanced model operations, optimizing performance, or ensuring data quality.

Calculates statistical power and required sample sizes for study planning. It supports both closed-form methods (for standard tests like t-tests, ANOVA) and simulation-based methods (for complex models like mixed models or survival analysis). Use this skill to determine the minimum detectable effect (MDE) or justify sample sizes for grants and IRB protocols before data collection.

This skill detects malicious, misspelled, or brand-jacked package names (typosquatting) across major ecosystems (npm, PyPI, crates.io). It uses advanced techniques like edit-distance and keyboard-proximity analysis, powered by tools like typomania and OSSGadget, to flag potential supply chain attacks *before* a dependency is installed. It is essential for implementing robust CI/CD security gates and proactive dependency screening.