- name
- running-r-analysis-in-existing-projects
- description
- Work inside an existing R project to extend analyses, modify scripts, run statistical models, update visualizations, and regenerate reports.
Running R Analysis in Existing Projects
This skill operates inside an already structured R project. It helps extend, debug, or enhance existing analyses without recreating the project from scratch.
Use this skill when the user wants to:
- Continue analysis in an existing R project
- Modify or extend R scripts
- Add new statistical models or tests
- Update plots or figures
- Regenerate reports after data or code changes
- Debug R errors in a project
What This Skill Does
When activated, this skill will:
- Understand the project structure
- Detect folders like data/, scripts/, results/, reports/ - Identify .Rproj, .Rmd, .qmd, or .R files
- Inspect existing analysis
- Read current scripts and reports - Identify which packages and methods are being used - Avoid rewriting working components unnecessarily
- Extend or modify analysis
- Add new models or statistical tests - Introduce new plots using ggplot2 - Add new data processing steps - Improve code structure or reproducibility
- Re-run and update outputs
- Recompute results - Overwrite or version new outputs in results/ - Re-render R Markdown or Quarto reports
- Debug issues
- Fix missing packages - Resolve file path problems - Handle common R errors and warnings
Example User Requests That Should Trigger This Skill
- "Add a survival analysis to this R project"
- "Update the plots in my report"
- "This R Markdown file throws an error, fix it"
- "Extend this analysis with a mixed-effects model"
- "Re-run everything after I updated the data"
Example Workflow
User: Add a logistic regression model and update the report.
Skill actions:
- Locate main analysis script
- Add logistic regression using
glm() - Save model summary to
results/ - Update report with new section and plot
- Re-render HTML/PDF report
Tools & Packages Commonly Used
| Purpose | R Packages |
|---|---|
| Data wrangling | tidyverse, dplyr |
| Modeling | stats, lme4, glmnet |
| Visualization | ggplot2 |
| Reporting | rmarkdown, quarto |
| Project management | here, renv |
Notes
- Respect the existing project structure and style
- Do not delete user code unless explicitly requested
- Prefer incremental updates over full rewrites
- Always regenerate reports after modifying analysis