
r-cli
Comprehensive R package for command-line interface styling, semantic messaging, and user communication. Use this skill when working with R code that needs to: (1) Format console output with inline markup and colors, (2) Display errors, warnings, or messages with cliabort/cliwarn/cliinform, (3) Show progress indicators for long-running operations, (4) Create semantic CLI elements (headers, lists, alerts, code blocks), (5) Apply themes and customize output styling, (6) Handle pluralization in user-facing text, (7) Work with ANSI strings, hyperlinks, or custom containers. Also use when migrating from base R message/warning/stop, debugging cli code, or improving existing cli usage.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/posit-dev/skills --skill r-cli- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads r-cli automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
CLI for R Packages
When to Use What
task: Display error with context and formatting
use: cli_abort() with inline markup and bullet lists
task: Show warning with formatting
use: cli_warn() with inline markup
task: Display informative message
use: cli_inform() with inline markup
task: Show progress for counted operations
use: cli_progress_bar() with total count
task: Show simple progress steps
use: cli_progress_step() with status messages
task: Format code or function names
use: {.code ...} or {.fn package::function}
task: Format file paths
use: {.file path/to/file}
task: Format package names
use: {.pkg packagename}
task: Format variable names
use: {.var variable_name}
task: Format values
use: {.val value}
task: Handle singular/plural text
use: {?s} or {?y/ies} with pluralization
task: Create headers
use: cli_h1(), cli_h2(), cli_h3()
task: Create alerts
use: cli_alert_success(), cli_alert_danger(), cli_alert_warning(), cli_alert_info()
task: Create lists
use: cli_ul(), cli_ol(), cli_dl() with cli_li()
Inline Markup Essentials
Use inline markup with {.class content} syntax to format text:
# Basic formatting
cli_text("Function {.fn mean} calculates averages")
cli_text("Install package {.pkg dplyr}")
cli_text("See file {.file ~/.Rprofile}")
cli_text("{.var x} must be numeric, not {.obj_type_of {x}}")
cli_text("Got value {.val {x}}")
# Code formatting
cli_text("Use {.code sum(x, na.rm = TRUE)}")
# Paths and arguments
cli_text("Reading from {.path /data/file.csv}")
cli_text("Set {.arg na.rm} to TRUE")
# Types and classes
cli_text("Object is {.cls data.frame}")
# Emphasis
cli_text("This is {.emph important}")
cli_text("This is {.strong critical}")
# Fields
cli_text("The {.field name} field is required")
Vector Collapsing
Vectors are automatically collapsed with commas and "and":
pkgs <- c("dplyr", "tidyr", "ggplot2")
cli_text("Installing packages: {.pkg {pkgs}}")
#> Installing packages: dplyr, tidyr, and ggplot2
files <- c("data.csv", "script.R")
cli_text("Found {length(files)} file{?s}: {.file {files}}")
#> Found 2 files: data.csv and script.R
Escaping Braces
Use double braces {{ and }} to escape literal braces:
cli_text("Use {{variable}} syntax in glue")
#> Use {variable} syntax in glue
For complete markup reference: See references/inline-markup.md for all 50+ inline classes, edge cases, nesting rules, and advanced patterns.
Pluralization Basics
Use {?} for pluralization with three patterns:
Single Alternative
nfile <- 1
cli_text("Found {nfile} file{?s}")
#> Found 1 file
nfile <- 3
cli_text("Found {nfile} file{?s}")
#> Found 3 files
Two Alternatives
ndir <- 1
cli_text("Found {ndir} director{?y/ies}")
#> Found 1 directory
ndir <- 5
cli_text("Found {ndir} director{?y/ies}")
#> Found 5 directories
Three Alternatives (zero/one/many)
nfile <- 0
cli_text("Found {nfile} file{?s}: {?no/the/the} file{?s}")
#> Found 0 files: no files
nfile <- 1
cli_text("Found {nfile} file{?s}: {?no/the/the} file{?s}")
#> Found 1 file: the file
nfile <- 3
cli_text("Found {nfile} file{?s}: {?no/the/the} file{?s}")
#> Found 3 files: the files
Helpers: qty() and no()
Use no() to display "no" instead of zero:
nfile <- 0
cli_text("Found {no(nfile)} file{?s}")
#> Found no files
Use qty() to set quantity explicitly:
nupd <- 3
ntotal <- 10
cli_text("{nupd}/{ntotal} {qty(nupd)} file{?s} {?needs/need} updates")
#> 3/10 files need updates
For advanced pluralization: See references/inline-markup.md for edge cases and complex patterns.
CLI Conditions: Core Patterns
Use cli conditions instead of base R for better formatting:
cli_abort() - Formatted Errors
# Before (base R)
stop("File not found: ", path)
# After (cli)
cli_abort("File {.file {path}} not found")
# With bullets for context
check_file <- function(path) {
if (!file.exists(path)) {
cli_abort(c(
"File not found",
"x" = "Cannot read {.file {path}}",
"i" = "Check that the file exists"
))
}
}
cli_warn() - Formatted Warnings
# Before (base R)
warning("Column ", col, " has missing values")
# After (cli)
cli_warn("Column {.field {col}} has missing values")
# With context
cli_warn(c(
"Data quality issues detected",
"!" = "Column {.field {col}} has {n_missing} missing value{?s}",
"i" = "Consider using {.fn tidyr::drop_na}"
))
cli_inform() - Formatted Messages
# Before (base R)
message("Processing ", n, " files")
# After (cli)
cli_inform("Processing {n} file{?s}")
# With structure
cli_inform(c(
"v" = "Successfully loaded {.pkg dplyr}",
"i" = "Version {packageVersion('dplyr')}"
))
Bullet Types
"x"- Error/problem (red X)"!"- Warning (yellow !)"i"- Information (blue i)"v"- Success (green checkmark)"*"- Bullet point">"- Arrow/pointer
For advanced error design: See references/conditions.md for error design principles, rlang integration, testing strategies, and real-world patterns.
Basic Progress Indicators
Simple Progress Steps
process_data <- function() {
cli_progress_step("Loading data")
data <- load_data()
cli_progress_step("Cleaning data")
clean <- clean_data(data)
cli_progress_step("Analyzing data")
analyze(clean)
}
Basic Progress Bar
process_files <- function(files) {
cli_progress_bar("Processing files", total = length(files))
for (file in files) {
process_file(file)
cli_progress_update()
}
}
Auto-Cleanup
Progress bars auto-close when the function exits:
process <- function() {
cli_progress_bar("Working", total = 100)
for (i in 1:100) {
Sys.sleep(0.01)
cli_progress_update()
}
# No need to call cli_progress_done() - auto-closes
}
For advanced progress: See references/progress.md for nested progress, custom formats, parallel processing, all progress variables, and Shiny integration.
Semantic CLI Elements
Headers
cli_h1("Main Section")
cli_h2("Subsection")
cli_h3("Detail")
Alerts
cli_alert_success("Operation completed successfully")
cli_alert_danger("Critical error occurred")
cli_alert_warning("Potential issue detected")
cli_alert_info("Additional information available")
Text and Code
# Regular text with markup
cli_text("This is formatted text with {.emph emphasis}")
# Code blocks
cli_code(c(
"library(dplyr)",
"mtcars %>% filter(mpg > 20)"
))
# Verbatim text (no formatting)
cli_verbatim("This is displayed exactly as-is: {not interpolated}")
Lists
# Unordered list
cli_ul()
cli_li("First item")
cli_li("Second item")
cli_end()
# Ordered list
cli_ol()
cli_li("First step")
cli_li("Second step")
cli_end()
# Definition list
cli_dl()
cli_li(c(name = "The name field"))
cli_li(c(email = "The email address"))
cli_end()
Common Workflows
Base R to CLI Migration
# Before: Base R error handling
validate_input <- function(x, y) {
if (!is.numeric(x)) {
stop("x must be numeric")
}
if (length(y) == 0) {
stop("y cannot be empty")
}
if (length(x) != length(y)) {
stop("x and y must have the same length")
}
}
# After: CLI error handling
validate_input <- function(x, y) {
if (!is.numeric(x)) {
cli_abort(c(
"{.arg x} must be numeric",
"x" = "You supplied a {.cls {class(x)}} vector",
"i" = "Use {.fn as.numeric} to convert"
))
}
if (length(y) == 0) {
cli_abort(c(
"{.arg y} cannot be empty",
"i" = "Provide at least one element"
))
}
if (length(x) != length(y)) {
cli_abort(c(
"{.arg x} and {.arg y} must have the same length",
"x" = "{.arg x} has length {length(x)}",
"x" = "{.arg y} has length {length(y)}"
))
}
}
Error Message with Rich Context
check_required_columns <- function(data, required_cols) {
actual_cols <- names(data)
missing_cols <- setdiff(required_cols, actual_cols)
if (length(missing_cols) > 0) {
cli_abort(c(
"Required column{?s} missing from data",
"x" = "Missing {length(missing_cols)} column{?s}: {.field {missing_cols}}",
"i" = "Data has {length(actual_cols)} column{?s}: {.field {actual_cols}}",
"i" = "Add the missing column{?s} or check for typos"
))
}
invisible(data)
}
Function with Progress Bar
process_files <- function(files, verbose = TRUE) {
n <- length(files)
if (verbose) {
cli_progress_bar(
format = "Processing {cli::pb_bar} {cli::pb_current}/{cli::pb_total} [{cli::pb_eta}]",
total = n
)
}
results <- vector("list", n)
for (i in seq_along(files)) {
results[[i]] <- process_file(files[[i]])
if (verbose) {
cli_progress_update()
}
}
results
}
Resources & Advanced Topics
Reference Files
-
references/inline-markup.md - Complete catalog of inline classes organized by category, advanced patterns, nesting rules, and real-world examples
-
references/conditions.md - Advanced error design patterns, rlang integration, testing with testthat snapshots, migration guide, and anti-patterns
-
references/progress.md - Nested progress bars, custom formats, all progress variables, parallel processing, Shiny integration, and debugging
-
references/themes.md - Complete theming system with CSS-like selectors, container functions, color palettes, custom themes, and accessibility
-
references/ansi-operations.md - ANSI string operations (align, columns, nchar, etc.), hyperlinks, color detection, testing CLI output, and troubleshooting
External Resources
Related Packages
- rlang - Condition handling and error objects integrate with cli
- glue - String interpolation powers cli's
{}syntax - testthat - Snapshot testing for cli output
FAQ
What does the r-cli skill do?
Comprehensive R package for command-line interface styling, semantic messaging, and user communication. Use this skill when working with R code that needs to: (1) Format console output with inline markup and colors, (2) Display errors, warnings, or messages with cliabort/cliwarn/cliinform, (3) Show progress indicators for long-running operations, (4) Create semantic CLI elements (headers, lists, alerts, code blocks), (5) Apply themes and customize output styling, (6) Handle pluralization in user-facing text, (7) Work with ANSI strings, hyperlinks, or custom containers. Also use when migrating from base R message/warning/stop, debugging cli code, or improving existing cli usage.
How do I install r-cli?
Run npx skills add https://github.com/posit-dev/skills --skill r-cli in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/r-cli/ (personal) or .claude/skills/r-cli/ (project).
Which AI agents can use r-cli?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is r-cli safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains r-cli?
It is published by posit-dev in posit-dev/skills. It has 73 recorded installs.
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