Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Interact with R and RStudio environments for scientific research tasks including creating projects, running analyses, managing dependencies, and generating p...
Interact with R and RStudio environments for scientific research tasks including creating projects, running analyses, managing dependencies, and generating p...
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
A Claude Code skill for comprehensive R-based research workflow automation. This skill enables interaction with R and RStudio environments for scientific computing, statistical analysis, bioinformatics, and data visualization.
This skill helps researchers and data scientists: Create structured, reproducible R research projects Execute R scripts and RMarkdown analyses Debug environment and dependency issues Generate publication-quality plots and reports Manage R packages with renv for reproducibility Use this skill when the user wants to: Create a new R project with standard structure Run R analyses on existing projects Troubleshoot R package dependencies Generate statistical reports or visualizations Set up reproducible R workflows
When activated, this skill provides four main capabilities:
Scaffold new R projects with standard folder structure Initialize Git repositories (optional) Set up renv for package management Generate template scripts and reports Create .Rproj files for RStudio
Execute R scripts and RMarkdown files Handle parameterized analyses Return results, tables, and plots Generate HTML/PDF reports
Check for missing R packages Resolve library conflicts Suggest fixes for environment issues Verify R version compatibility
Create figures with ggplot2 and other visualization libraries Export to PDF/PNG/SVG/TIFF formats Follow journal-specific formatting guidelines Support multi-panel composite figures Use color-blind friendly palettes
"Create a new R project for my genomics data analysis" "Run analysis.R in my existing project and show results" "Check if all required packages are installed" "Generate a scatter plot with regression line from my dataset" "Set up a reproducible R workflow for RNA-seq analysis" "Debug my R environment - packages won't load" "Create a statistical report for this clinical trial data"
Projects created by this skill follow this standardized structure: my-research-project/ โโโ data/ โ โโโ raw/ # Original, immutable data files โ โโโ processed/ # Cleaned, transformed data โโโ scripts/ # Analysis and processing scripts โโโ results/ โ โโโ figures/ # Plots and visualizations โ โโโ tables/ # Summary tables โ โโโ models/ # Saved model objects (.rds files) โโโ reports/ # R Markdown/Quarto documents โโโ renv.lock # Package version lock file โโโ .Rproj # RStudio project file โโโ README.md # Project documentation
PurposeR PackagesData wranglingtidyverse, data.tableVisualizationggplot2, patchwork, scalesStatisticsstats, lme4, survival, broomBioinformaticsBioconductor (DESeq2, edgeR, limma)Reportingrmarkdown, quartoReproducibilityrenv
User: Create a new R project for gene expression analysis with Git initialized. Skill actions: Create directory structure (data/, scripts/, results/, reports/) Initialize Git repository Set up renv environment Install DESeq2, tidyverse, ggplot2 Generate analysis template scripts Create R Markdown report template
User: Run the differential expression analysis and return results. Skill actions: Activate project environment (renv) Execute analysis script Capture console output and plots Return summary tables and model statistics Generate report if requested
User: My R script fails with "package not found" errors. Skill actions: Check R version and package library paths Scan script for required packages Compare with installed packages Generate installation commands Check for version conflicts
Requires R >= 4.0.0 Supports both RStudio and command-line R Uses renv for reproducible package management All outputs saved to files (not just console) Follows R best practices and modern conventions
This skill includes specialized sub-skills: create-project: Scaffold new R research projects run-analysis: Execute R scripts and generate reports debug-env: Troubleshoot R environments and dependencies generate-plots: Create publication-quality figures with journal formatting Each sub-skill can be invoked independently or as part of a complete workflow.
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Largest current source with strong distribution and engagement signals.