R Cran Status logo

R Cran Status

Organization
posit-dev
r-cran-status

Look up an R package's live status on cran.r-project.org - submission/review state (queue, human review, waiting, archived, past version's fate) or R CMD check results (OK/NOTE/WARN/ERROR per platform). Use for "what's the CRAN status of X", "did X get accepted/rejected", "is X passing CRAN checks", "when was version Y archived".

Overview

Publisherposit-dev
Repositoryskills
Skill namer-cran-status
Stars
516
Forks
53
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the R Cran Status 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/r-cran-status .claude/skills/r-cran-status
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable R Cran Status 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 R Cran Status 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 R Cran Status 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.

CRAN Package Status

Check a package's submission/review state, a specific historical version's fate (e.g. {package} {version}, as in btw v1.4.0), or its current R CMD check results across CRAN's test platforms.

"CRAN status" is ambiguous between two questions:

  • Submission status: is/was this package (or version) in review, published, archived, or rejected? See "Submission Status".
  • Check results: is the published version passing R CMD check on all platforms, or does it have WARN/ERROR/NOTE flags risking removal? See "Check Results".

CRAN's servers are a shared, unpaid resource. Never issue requests in parallel or in a tight loop — pause briefly (e.g. sleep 1) between requests, stop looping as soon as a match is found, and avoid re-fetching a page you've already checked in this session.

Workflow

  1. Ask for the package name if not provided. A version may also be given (e.g. btw v1.4.0 or btw 1.4.0); strip any leading v.
  2. Decide which question is being asked:
    • Version given, or request mentions submission, review, the queue, or rejection/archival → Submission Status.
    • Request mentions checks, R CMD check, WARN/ERROR/NOTE, or platforms/flavors → Check Results.
    • If genuinely ambiguous (e.g. just "check the CRAN status of x"), ask which is meant, or check both and report both.
  3. Follow the relevant section below and report the result.

Submission Status

  1. Check the currently published version first (see below).
  2. If no version was requested, or it matches the current version: report it as the current, published release. Skip to step 5 unless it's absent from PACKAGES, in which case continue to step 3.
  3. If a prior check this conversation already located the package in a stage or reviewer folder, check that folder first, then forward from it in the pipeline order (see "CRAN Review Stages") — don't re-sweep from the start. Otherwise, sweep all stage and reviewer folders.
  4. Search the incoming/ stage folders (see below).
  5. Search the reviewer-assigned folders (see below).
  6. If a specific version was requested and doesn't match the current published version (or the package isn't published at all), check the CRAN Archive for that version (see below).
  7. Report the result (see "Reporting Submission Status Results").

CRAN Review Stages

Listed in typical pipeline order — a package usually moves top to bottom, though not every package passes through every stage:

  • inspect / newbies: awaiting initial manual inspection (newbies is for first-time submitters)
  • pending: awaiting closer review
  • human/<initials>: assigned to a CRAN reviewer
  • pretest: automated checks (re)running
  • waiting: CRAN is waiting for a maintainer response (loops back to pretest once the maintainer responds)
  • recheck: reverse-dependency checks
  • publish: approved and awaiting publication
  • archive: rejected

Checking Incoming Stage Folders

Replace {package} with the actual package name. Start at the last-known stage if one exists (see Submission Status step 3), else at inspect:

sh
for stage in inspect newbies pending pretest waiting recheck publish archive; do
  curl -Ls "https://cran.r-project.org/incoming/$stage/" |
    grep -Eio '[^"]*{package}[^"]*' &&
    echo "Stage: $stage" && break
  sleep 1
done

Checking Reviewer-Assigned Folders

Reviewer-initials folders (e.g. human/KH) change as CRAN's team changes, so discover them from the incoming/ listing instead of a fixed set: any folder there that isn't one of the stage names above is a reviewer folder.

sh
reviewer_folders=$(
  curl -Ls "https://cran.r-project.org/incoming/" |
    grep -Eio '<a href="[^"]+/">' |
    sed -E 's/<a href="([^"]+)\/">/\1/' |
    grep -Ev '^(inspect|newbies|pending|pretest|publish|recheck|archive|waiting|special)$'
)

for stage in $reviewer_folders; do
  curl -Ls "https://cran.r-project.org/incoming/$stage/" |
    grep -Eio '[^"]*{package}[^"]*' &&
    echo "Stage: human/$stage" && break
  sleep 1
done

Checking Whether the Package Is Already Published

sh
curl -Ls https://cran.r-project.org/src/contrib/PACKAGES |
  awk -v pkg="{package}" '
    $0 == "Package: " pkg { found=1 }
    found && /^Version:/ { print; exit }
  '

A printed Version: line is the current CRAN version. Remember it — needed later to say whether a requested older version was "superseded by" it.

Checking a Specific Version in the CRAN Archive

Superseded versions move out of src/contrib/ into a per-package archive folder. This Archive is unrelated to the archive incoming/ stage above (that means "rejected"; this means "an older version, since superseded").

sh
curl -Ls "https://cran.r-project.org/src/contrib/Archive/{package}/" |
  grep -Eio '[^"]*{package}_{version}\.tar\.gz[^"]*'

A matching .tar.gz filename means that exact version was published and has since been superseded.

Reporting Submission Status Results

  • No version requested:
    • Present in PACKAGES: report as published, with current version.
    • Else found in an incoming/ or reviewer folder: report the folder name and meaning from the stage list above.
    • Else: report it wasn't found in CRAN's submission queue or index.
  • Specific version requested:
    • Matches current version in PACKAGES: report as the current release.
    • Else found in the CRAN Archive: report it was published and has been superseded by the current version (from PACKAGES), e.g. "available in the archive, superseded by v1.5.0".
    • Else the package (any version) is found in an incoming/ or reviewer folder: report that stage, noting the requested version wasn't a past release.
    • Else: report the requested version wasn't found (current, archived, or in-review).

Check Results

CRAN publishes per-platform R CMD check results for every published package at https://cran.r-project.org/web/checks/check_results_{package}.html. WARN or ERROR results persisting more than ~2-4 weeks risk archival by CRAN.

Fetch and simplify the results table:

sh
curl -Ls "https://cran.r-project.org/web/checks/check_results_{package}.html" |
  grep '<tr> <td>' |
  sed -E 's/<[^>]+>/ /g' |
  awk '{print $1": "$NF}'

Prints one flavor: STATUS line per row, e.g.:

r-devel-linux-x86_64-debian-clang: OK
r-oldrel-windows-x86_64: ERROR

Status is OK, NOTE, WARN, or ERROR. For any non-OK flavor, full failure output is further down the same page under "Check Details" — fetch again without stripping tags and read the <pre>-formatted section after the failing flavor's Version: / Check: / Result: lines.

A 404 means no CRAN check history — likely not currently published. Check submission status instead.

Reporting Check Results

  • Every flavor OK: report the package passes checks on all platforms.
  • Any flavor NOTE/WARN/ERROR: list affected flavors and status, summarize failure reason(s) from "Check Details", and note that persistent WARN/ERROR can lead to archival.
  • Page 404s: report no check results exist; check/report submission status instead.

Frequently asked questions

What does the R Cran Status AI skill do?

Look up an R package's live status on cran.r-project.org - submission/review state (queue, human review, waiting, archived, past version's fate) or R CMD check results (OK/NOTE/WARN/ERROR per platform). Use for "what's the CRAN status of X", "did X get accepted/rejected", "is X passing CRAN checks", "when was version Y archived".

Why use R Cran Status on TypingMind?

Because you install it once and use it with any model. R Cran Status 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 R Cran Status in TypingMind?

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

Which AI models can use R Cran Status?

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 R Cran Status?

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

Is the R Cran Status 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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