rstudio-research-agent - SKILL.md Agent Skill

name: rstudio-research-agent

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

RStudio Research Agent

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:


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:

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

Running an Analysis

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

Debugging Dependencies

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

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.