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Fastverse R

Category: Science & Research  ·  Sub-category: math-stats  ·  Last updated:
Expert guidance for the fastverse in R — the high-performance suite built on data.table, collapse, kit and magrittr, loaded with library(fastverse). Covers how the loader itself works (fastverse_extend/detach/reset/sitrep/ update/child, .fastverse project config files, options, OpenMP threading across the three multithreaded packages), the kit API (psum/pmean/pfirst/ plast/fpmin/fpmax/prange/pany/pall/pcount parallel statistical functions, vswitch/nswitch vectorized and nested switches, iif/nif, topn, charToFact, countOccur, uniqLen, setlevels, psort), the data.table API ([i, j, by], := and set() reference updates, .SD/.N/.I/.GRP/.BY, GForce, froll* rolling functions, keyed/rolling/non-equi joins and foverlaps, fread/fwrite, set* helpers, copy/rowid/rleid/setattr/transpose/nafill/shift), the magrittr operators (%>%, %<>%, %$%, %T>%, extract, set_names), and above all HOW THE FOUR PACKAGES DIVIDE THE WORK — when to reach for collapse versus data.table versus kit, with measured timings. Use this skill WHENEVER the user is writing or reviewing R code that loads the fastverse, data.table, collapse or kit; whenever they mention fastverse, data.table, kit, magrittr, .fastverse files, fastverse_extend, setDTthreads, kit.nThread, DT[i, j, by], :=, .SD, GForce, frollmean/frollapply, rolling or non-equi joins, fread/fwrite, psum/pmean/topn/vswitch/nswitch/iif/nif; and whenever they ask which of these packages to use for a task, how to combine them, or how to speed up an R data pipeline. Also use it when translating dplyr/base R/pandas code to a fast R stack, when a script mixes data.table and collapse, and when working with large data, panels, matrices, or spatial (sf) data frames in R. REQUIRES the companion skill collapse-r, which documents the collapse API itself. This skill deliberately does not duplicate it: it covers the other three packages, the loader, and the division of labour between all four. Load collapse-r alongside this one and delegate to it for anything that turns on how a collapse function behaves.
Security AStatic scan found no risk patternsHow grading works ›

From the source SKILL.md

library(fastverse) attaches four packages that were chosen to work together:

What this skill does

Fastverse R is a community-contributed Claude Code skill in the math-stats sub-category. It ships as a SKILL.md file that Claude Code auto-discovers under ~/.claude/skills/fastverse-r/ and loads when your prompt matches the skill's trigger.

Who uses this skill

The Fastverse R Claude Code skill is built for researchers, data scientists, academics, and analysts working with complex data and scientific literature. It's part of ClaudSkills (also referred to as Claude Skills or Claude Code Skills) — the open community-curated registry of 186,000+ SKILL.md files for Anthropic's Claude Code agent and the wider Claude ecosystem (Claude API, Claude Agent SDK).

How to install

Free

Manual install (2 steps)

mkdir -p ~/.claude/skills/fastverse-r
curl -L https://claudskills.com/skills/fastverse-r/SKILL.md \
  -o ~/.claude/skills/fastverse-r/SKILL.md

Or just download SKILL.md directly and drop it into ~/.claude/skills/fastverse-r/. Claude Code auto-discovers it on next session.

Skills live at ~/.claude/skills/fastverse-r/SKILL.md on macOS/Linux, or %USERPROFILE%\.claude\skills\fastverse-r\SKILL.md on Windows. See the full install guide for step-by-step instructions.

Telegram

📱 Install from your phone or desktop Telegram

Open @claudskills_bot on Telegram, tap Open Desktop App, and the desktop app installs this skill for you. Or share the bot link with a colleague — they get the same one-tap install. Learn more →

Pro

One-click install via the desktop app

The ClaudSkills desktop app installs any skill directly into ~/.claude/skills/ with one click — no terminal required. Pro starts at $9/mo or $149 lifetime.

Pro

For the full experience including quality scoring and one-click install features for each skill — upgrade to Pro.

Frequently asked questions

How do I install the Fastverse R Claude Code skill?
Install via the ClaudSkills desktop app (one click) or copy SKILL.md from the source repository to ~/.claude/skills/fastverse-r/SKILL.md and restart Claude Code. Both flows are detailed at claudskills.com/install/.
What does the Fastverse R skill do?
Expert guidance for the fastverse in R — the high-performance suite built on data.table, collapse, kit and magrittr, loaded with library(fastverse). Covers how the loader itself works (fastverse_extend/detach/reset/sitrep/ update/child, .fastverse project config files, options, OpenMP threading across the three multithreaded packages), the kit API (psum/pmean/pfirst/ plast/fpmin/fpmax/prange/pany/pall/pcount parallel statistical functions, vswitch/nswitch vectorized and nested switches, iif/nif, topn, charToFact, countOccur, uniqLen, setlevels, psort), the data.table API ([i, j, by], := and set() reference updates, .SD/.N/.I/.GRP/.BY, GForce, froll* rolling functions, keyed/rolling/non-equi joins and foverlaps, fread/fwrite, set* helpers, copy/rowid/rleid/setattr/transpose/nafill/shift), the magrittr operators (%>%, %<>%, %$%, %T>%, extract, set_names), and above all HOW THE FOUR PACKAGES DIVIDE THE WORK — when to reach for collapse versus data.table versus kit, with measured timings. Use this skill WHENEVER the user is writing or reviewing R code that loads the fastverse, data.table, collapse or kit; whenever they mention fastverse, data.table, kit, magrittr, .fastverse files, fastverse_extend, setDTthreads, kit.nThread, DT[i, j, by], :=, .SD, GForce, frollmean/frollapply, rolling or non-equi joins, fread/fwrite, psum/pmean/topn/vswitch/nswitch/iif/nif; and whenever they ask which of these packages to use for a task, how to combine them, or how to speed up an R data pipeline. Also use it when translating dplyr/base R/pandas code to a fast R stack, when a script mixes data.table and collapse, and when working with large data, panels, matrices, or spatial (sf) data frames in R. REQUIRES the companion skill collapse-r, which documents the collapse API itself. This skill deliberately does not duplicate it: it covers the other three packages, the loader, and the division of labour between all four. Load collapse-r alongside this one and delegate to it for anything that turns on how a collapse function behaves.
Is this skill free to install?
Yes. ClaudSkills is an open registry — every skill keeps its source repository's license, and manual install via copy is free. ClaudSkills Pro ($9/mo, $79/yr, or $149 one-time) adds one-click install via the desktop app and a multi-signal Quality Score.
When should I use the Fastverse R skill?
Use Fastverse R when your Claude Code task falls under the Science & Research category — specifically in the math stats area. Claude Code auto-discovers installed skills and invokes the right one based on the task description, so you can also ask Claude directly (e.g. "use Fastverse R" or describe the task and let Claude pick). Browse related skills at /category/science/.
What is a Claude Code skill and how does the Fastverse R skill fit in?
A Claude Code skill is a SKILL.md file that lives under ~/.claude/skills/<name>/ and tells the Claude Code CLI agent how to perform a specific task (instructions, prompts, allowed tools). Skills are auto-discovered at session start. Fastverse R is one of 67,000+ skills indexed in the open ClaudSkills catalog, classified under the Science & Research category. Learn more at /learn/what-is-a-claude-skill/.

Attribution & license

Cite this skill

If you reference this skill in a blog post, paper, or documentation, you can cite it as:

APA
fastverse. (2026). Fastverse R [Claude Code skill]. ClaudSkills. https://claudskills.com/skills/fastverse-r/
BibTeX
@misc{fastverse-r-2026,
  author    = {fastverse},
  title     = {Fastverse R [Claude Code skill]},
  year      = {2026},
  publisher = {ClaudSkills},
  url       = {https://claudskills.com/skills/fastverse-r/}
}

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Security scan

Grade A · scanned 2026-08-15 — free static scan against the OWASP Agentic Skills Top 10.

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