claude-code-r-skills: Skill for Claude Code

Test-Driven Development Workflow for R

This skill ensures all R code development follows TDD principles with comprehensive test coverage using testthat.

When to Activate

• Writing new functions or features
• Fixing bugs or issues
• Refactoring existing code
• Adding new model types
• Creating data processing pipelines
• Building Shiny components

Getting Started

Initialize testing infrastructure for your package:

# Set up testthat (Edition 3)
usethis::use_testthat(3)

# Create a test file for an existing source file
usethis::use_test("function_name")

# Or create test and source file together
usethis::use_r("function_name")
usethis::use_test("function_name")

Core Principles

1. Tests BEFORE Code

ALWAYS write tests first, then implement code to make tests pass.

2. Coverage Requirements

• Minimum 80% coverage (unit + integration)
• 100% coverage for statistical calculations
• 100% coverage for data validation
• All edge cases covered
• Error scenarios tested

3. Test Types

Tests follow a three-level hierarchy: File → Test → Expectation

Unit Tests

Individual functions and utilities:

test_that("rescale01 normalizes to [0, 1] range", {
  expect_equal(rescale01(c(0, 5, 10)), c(0, 0.5, 1))
  expect_equal(rescale01(c(-10, 0, 10)), c(0, 0.5, 1))
})

test_that("rescale01 handles edge cases", {
  expect_equal(rescale01(c(5, 5, 5)), c(NaN, NaN, NaN))
  expect_equal(rescale01(numeric(0)), numeric(0))
  expect_equal(rescale01(c(0, NA, 10)), c(0, NA, 1))
})

Integration Tests

Function interactions and workflows:

test_that("data pipeline produces expected output", {
  raw_data <- read_fixture("sample_input.csv")

  result <- raw_data |>
    clean_data() |>
    transform_features() |>
    summarize_results()

  expect_s3_class(result, "tbl_df")
  expect_named(result, c("group", "mean", "sd", "n"))
  expect_true(all(result$n > 0))
})

Snapshot Tests

For complex outputs that are hard to specify:

test_that("model summary format is stable", {
  model <- fit_model(test_data)
  expect_snapshot(print(summary(model)))
})

test_that("error messages are informative", {
  expect_snapshot(
    validate_input(invalid_data),
    error = TRUE
  )
})