Skip to content
TrustedSkillsbeta
Back to all skills

Ggplot2

Checked
jsperger·vlatest·data·MIT

Generates interactive visualizations from R data using ggplot2, enabling insightful data exploration and clear communication of findings.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add jsperger/llm-r-skills --skill ggplot2 -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

jsperger

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned jsperger/llm-r-skills at 7a10126faf.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
7a10126faf
Manifest
skills/ggplot2/SKILL.md
Scanned
1 file, 315 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

The ggplot2 skill enables AI agents to create visually appealing and informative statistical graphics in R. It leverages the popular ggplot2 package, allowing for the generation of a wide variety of plots including scatterplots, histograms, bar charts, and boxplots. Agents can use this skill to explore data patterns, communicate findings effectively, and build interactive visualizations.

When to use it

  • Data Exploration: Generate quick visualizations to understand the distribution and relationships within a dataset.
  • Report Generation: Create professional-looking plots for inclusion in reports or presentations.
  • Interactive Dashboards: Build dynamic dashboards where users can interact with data through visual representations.
  • Scientific Research: Produce publication-quality figures for scientific papers and research projects.

Key capabilities

  • Generates various plot types (scatterplots, histograms, bar charts, boxplots).
  • Utilizes the ggplot2 R package.
  • Creates visually appealing and informative graphics.
  • Supports data exploration and communication of findings.

Example prompts

  • "Create a scatterplot showing the relationship between X and Y in this dataset."
  • "Generate a histogram of the 'age' column from my data."
  • "Produce a bar chart comparing sales across different product categories."

Tips & gotchas

  • Requires an R environment to be available for the AI agent.
  • The quality of the visualization depends on the structure and cleanliness of the input dataset.