Lifecycle logo

Lifecycle

Organization
posit-dev
lifecycle

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functions, (5) Marking functions as experimental, (6) Understanding lifecycle stages (stable, experimental, deprecated, superseded), or (7) Writing deprecation helpers for complex scenarios.

Overview

Publisherposit-dev
Repositoryskills
Skill namelifecycle
Stars
516
Forks
53
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by posit-dev on GitHub. Read the source before you install it.

Installation

Install the Lifecycle AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/posit-dev/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/r-lib/lifecycle .claude/skills/lifecycle
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Lifecycle in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Lifecycle on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Lifecycle is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

R Package Lifecycle Management

Manage function and argument lifecycle using tidyverse conventions and the lifecycle package.

Setup

Check if lifecycle is configured by looking for lifecycle-*.svg files in man/figures/.

If not configured, run:

r
usethis::use_lifecycle()

This:

  • Adds lifecycle to Imports in DESCRIPTION
  • Adds @importFrom lifecycle deprecated to the package documentation file
  • Copies badge SVGs to man/figures/

Lifecycle Badges

Insert badges in roxygen2 documentation:

r
#' @description
#' `r lifecycle::badge("experimental")`
#' `r lifecycle::badge("deprecated")`
#' `r lifecycle::badge("superseded")`

For arguments:

r
#' @param old_arg `r lifecycle::badge("deprecated")` Use `new_arg` instead.

Only badge functions/arguments whose stage differs from the package's overall stage.

Deprecating a Function

  1. Add badge and explanation to @description:
r
#' Do something
#'
#' @description
#' `r lifecycle::badge("deprecated")`
#'
#' `old_fun()` was deprecated in mypkg 1.0.0. Use [new_fun()] instead.
#' @keywords internal
  1. Add deprecate_warn() as first line of function body:
r
old_fun <- function(x) {

lifecycle::deprecate_warn("1.0.0", "old_fun()", "new_fun()")
new_fun(x)
}
  1. Show migration in examples:
r
#' @examples
#' old_fun(x)
#' # ->
#' new_fun(x)

Deprecation Functions

FunctionWhen to Use
deprecate_soft()First stage; warns only direct users and during tests
deprecate_warn()Standard deprecation; warns once per 8 hours
deprecate_stop()Final stage before removal; errors with helpful message

Deprecation workflow for major releases:

  1. Search deprecate_stop() - consider removing function entirely
  2. Replace deprecate_warn() with deprecate_stop()
  3. Replace deprecate_soft() with deprecate_warn()

Renaming a Function

Move implementation to new name, call from old name with deprecation:

r
#' @description
#' `r lifecycle::badge("deprecated")`
#'
#' `add_two()` was renamed to `number_add()` for API consistency.
#' @keywords internal
#' @export
add_two <- function(x, y) {
lifecycle::deprecate_warn("1.0.0", "add_two()", "number_add()")
number_add(x, y)
}

#' Add two numbers
#' @export
number_add <- function(x, y) {
x + y
}

Deprecating an Argument

Use deprecated() as default value with is_present() check:

r
#' @param path `r lifecycle::badge("deprecated")` Use `file` instead.
write_file <- function(x, file, path = deprecated()) {
  if (lifecycle::is_present(path)) {
    lifecycle::deprecate_warn("1.4.0", "write_file(path)", "write_file(file)")
    file <- path
  }
  # ... rest of function
}

Renaming an Argument

r
add_two <- function(x, y, na_rm = TRUE, na.rm = deprecated()) {
  if (lifecycle::is_present(na.rm)) {
    lifecycle::deprecate_warn("1.0.0", "add_two(na.rm)", "add_two(na_rm)")
    na_rm <- na.rm
  }
  sum(x, y, na.rm = na_rm)
}

Superseding a Function

For functions with better alternatives that shouldn't be removed:

r
#' Gather columns into key-value pairs
#'
#' @description
#' `r lifecycle::badge("superseded")`
#'
#' Development on `gather()` is complete. For new code, use [pivot_longer()].
#'
#' `df %>% gather("key", "value", x, y, z)` is equivalent to
#' `df %>% pivot_longer(c(x, y, z), names_to = "key", values_to = "value")`.

No warning needed - just document the preferred alternative.

Marking as Experimental

r
#' @description
#' `r lifecycle::badge("experimental")`
cool_function <- function() {
  lifecycle::signal_stage("experimental", "cool_function()")
  # ...
}

Testing Deprecations

Test that deprecated functions work and warn appropriately:

r
test_that("old_fun is deprecated", {
  expect_snapshot({
    x <- old_fun(1)
    expect_equal(x, expected_value)
  })
})

Suppress warnings in existing tests:

r
test_that("old_fun returns correct value", {
  withr::local_options(lifecycle_verbosity = "quiet")
  expect_equal(old_fun(1), expected_value)
})

Deprecation Helpers

For deprecations affecting many functions (e.g., removing a common argument), create an internal helper:

r
warn_for_verbose <- function(
  verbose = TRUE,
  env = rlang::caller_env(),
  user_env = rlang::caller_env(2)
) {
  if (!lifecycle::is_present(verbose) || isTRUE(verbose)) {
    return(invisible())
  }

  lifecycle::deprecate_warn(
    when = "2.0.0",
    what = I("The `verbose` argument"),
    details = c(
      "Set `options(mypkg_quiet = TRUE)` to suppress messages.",
      "The `verbose` argument will be removed in a future release."
    ),
    user_env = user_env
  )

  invisible()
}

Then use in affected functions:

r
my_function <- function(..., verbose = deprecated()) {
  warn_for_verbose(verbose)
  # ...
}

Custom Deprecation Messages

For non-standard deprecations, use I() to wrap custom text:

r
lifecycle::deprecate_warn(
  when = "1.0.0",
  what = I('Setting option "pkg.opt" to "foo"'),
  with = I('"pkg.new_opt"')
)

The what fragment must work with "was deprecated in..." appended.

Reference

See references/lifecycle-stages.md for detailed stage definitions and transitions.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Lifecycle AI skill do?

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.

Why use Lifecycle on TypingMind?

Because you install it once and use it with any model. Lifecycle is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Lifecycle in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/posit-dev/skills/tree/main/r-lib/lifecycle. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Lifecycle?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Lifecycle?

As many as you like. As long as a model supports skills, you can use Lifecycle with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Lifecycle AI skill free?

Yes. It is published on GitHub by posit-dev under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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