metaprogramming
R Metaprogramming with rlang
Metaprogramming is the ability to defuse, create, and inject R expressions. The core pattern is defuse-and-inject: capture code as data, optionally transform it, then inject it into another context for evaluation.
Quick Reference
More from jsperger/llm-r-skills
ggplot2
Use when working with R ggplot2 package, especially ggplot2 4.0+ features. Covers S7 migration (@ property access), theme defaults with ink/paper/accent, element_geom(), from_theme(), theme shortcuts (theme_sub_*), palette themes, labels with dictionary/attributes, discrete scale improvements (palette, continuous.limits, minor_breaks, sec.axis), position aesthetics (nudge_x/nudge_y, order), facet_wrap dir/space/layout, boxplot/violin/label styling, stat_manual(), stat_connect(), coord reversal.
41rlang-conditions
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13targets-pipelines
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12hardhat
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11tidy-evaluation
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11tidymodels-overview
This skill should be used when working with R tidymodels packages, including when the user asks to "create a tidymodels workflow", "build a recipe", "tune a model", "use parsnip", "set up resampling", "create a workflow_set", "compare models", "stack models", or mentions tidymodels packages like recipes, parsnip, workflows, workflowsets, tune, rsample, yardstick, or stacks. Provides ecosystem context before package-specific skills.
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