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Found 5 Skills
Guidance for managing R package lifecycle according to tidyverse principles using the lifecycle package. Use when: (1) Setting up lifecycle infrastructure in a package, (2) Deprecating functions or arguments, (3) Renaming functions or arguments, (4) Superseding functions, (5) Marking functions as experimental, (6) Understanding lifecycle stages (stable, experimental, deprecated, superseded), or (7) Writing deprecation helpers for complex scenarios.
R programming for data analysis, visualization, and statistical workflows. Use when working with R scripts (.R), Quarto documents (.qmd), RMarkdown (.Rmd), or R projects. Covers tidyverse workflows, ggplot2 visualizations, statistical analysis, epidemiological methods, and reproducible research practices.
Create professional package release blog posts following Tidyverse or Shiny blog conventions. Use when the user needs to: (1) Write a release announcement blog post for an R or Python package for tidyverse.org or shiny.posit.co, (2) Transform NEWS/changelog content into blog format, (3) Generate acknowledgments sections with contributor lists, (4) Format posts following specific blog platform requirements. Supports both Tidyverse (hugodown) and Shiny (Quarto) blog formats with automated contributor fetching and comprehensive style guidance.
R 4.4+ development specialist covering tidyverse, ggplot2, Shiny, and data science patterns. Use when developing data analysis pipelines, visualizations, or Shiny applications.
R statistical programming for data analysis, visualization, and modeling. Use for .r files.