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base-r-skill

Provides base R programming guidance covering data structures, data wrangling, statistical modeling, visualization, and I/O

iremaydas/base-r-skillcommunitylistedunreviewed
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Set up

Skills are installed by placing their folder where your agent loads skills.

Download ZIP from GitHub Open the repository

The download comes from github.com/iremaydas/base-r-skill itself, not from our server, so what you get is exactly what its author published.

Install instructions come from the README

Skills do not use an MCP config. Follow the steps in the README below.

README

synced Oct 20, 2026

base-r-skill

A Claude Code skill for base R programming.

The Story

I'm a political science PhD candidate who uses R regularly but would never call myself an R person. I needed a Claude Code skill for base R — something without tidyverse, without ggplot2, just plain R — and I couldn't find one anywhere.

So I made one myself. At 11pm. Asking Claude to help me build a skill for Claude.

If you're also someone who Googles how to drop NA rows in R every single time, this one's for you. 🫶

What's Inside

base-r/
├── SKILL.md                    # Main skill file
├── references/                 # Gotchas & non-obvious behaviors
│   ├── data-wrangling.md       # Subsetting traps, apply family, merge, factor quirks
│   ├── modeling.md             # Formula syntax, lm/glm/aov/nls, optim
│   ├── statistics.md           # Hypothesis tests, distributions, clustering
│   ├── visualization.md        # par, layout, devices, colors
│   ├── io-and-text.md          # read.table, grep, regex, format
│   ├── dates-and-system.md     # Date/POSIXct traps, options(), file ops
│   └── misc-utilities.md       # tryCatch, do.call, time series, utilities
├── scripts/
│   ├── check_data.R            # Quick data quality report for any data frame
│   └── scaffold_analysis.R     # Generates a starter analysis script
└── assets/
    └── analysis_template.R     # Copy-paste analysis template

The reference files were condensed from the official R 4.5.3 manual — 19,518 lines → 945 lines (95% reduction). Only the non-obvious stuff survived: gotchas, surprising defaults, tricky interactions. The things Claude already knows well got cut.

How to Use

Add this skill to your Claude Code setup by pointing to this repo. Then Claude will automatically load the relevant reference files when you're working on R tasks.

Works best for:

  • Base R data manipulation (no tidyverse)
  • Statistical modeling with lm, glm, aov
  • Base graphics with plot, par, barplot
  • Understanding why your R code is doing that weird thing

Not for: tidyverse, ggplot2, Shiny, or R package development.

The check_data.R Script

Probably the most useful standalone thing here. Source it and run check_data(df) on any data frame to get a formatted report of dimensions, NA counts, numeric summaries, and categorical breakdowns.

source("scripts/check_data.R")
check_data(your_df)

Built With Help From

  • Claude (obviously)
  • The official R manuals (all 19,518 lines of them)
  • Mild frustration and several cups of coffee

Contributing

If you spot a missing gotcha, a wrong default, or something that should be in the references — PRs are very welcome. I'm learning too.

Made by @iremaydas — PhD candidate, occasional R user, full-time Googler of things I should probably know by now.

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