Rstudio Research Agent

Interact with R and RStudio environments for scientific research tasks including creating projects, running analyses, managing dependencies, and generating publication-quality plots.

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.

Overview

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

---

What This Skill Does

When activated, this skill provides four main capabilities:

1. Create R Research Projects

• 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

2. Run Analyses in Existing Projects

• Execute R scripts and RMarkdown files
• Handle parameterized analyses
• Return results, tables, and plots
• Generate HTML/PDF reports

3. Debug Environment and Dependencies

• Check for missing R packages
• Resolve library conflicts
• Suggest fixes for environment issues
• Verify R version compatibility

4. Generate Publication-Quality Plots

• 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

---

Example User Requests That Should Trigger This Skill

• "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"

---

Project Structure

Projects created by this skill follow this standardized structure:

text

my-research-project/
├── data/
│   ├── raw/               # Original, immutable data files
│   └── processed/         # Cleaned, transformed data
├── scripts/               # Analysis and processing scripts
├── results/
│   ├── figures/           # Plots and visualizations
│   ├── tables/            # Summary tables
│   └── models/            # Saved model objects (.rds files)
├── reports/               # R Markdown/Quarto documents
├── renv.lock              # Package version lock file
├── .Rproj                 # RStudio project file
└── README.md              # Project documentation

---

Tools & Packages Commonly Used

Purpose	R Packages
Data wrangling	tidyverse, data.table
Visualization	ggplot2, patchwork, scales
Statistics	stats, lme4, survival, broom
Bioinformatics	Bioconductor (DESeq2, edgeR, limma)
Reporting	rmarkdown, quarto
Reproducibility	renv

---

Example Workflows

Creating a New Project

User: Create a new R project for gene expression analysis with Git initialized.

Skill actions:

1. Create directory structure (data/, scripts/, results/, reports/)
2. Initialize Git repository
3. Set up renv environment
4. Install DESeq2, tidyverse, ggplot2
5. Generate analysis template scripts
6. Create R Markdown report template

Running an Analysis

User: Run the differential expression analysis and return results.

Skill actions:

1. Activate project environment (renv)
2. Execute analysis script
3. Capture console output and plots
4. Return summary tables and model statistics
5. Generate report if requested

Debugging Dependencies

User: My R script fails with "package not found" errors.

Skill actions:

1. Check R version and package library paths
2. Scan script for required packages
3. Compare with installed packages
4. Generate installation commands
5. Check for version conflicts

---

Notes

• 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

---

Sub-Skills

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.