r-engineering

This skill improves R code for analysis, pipelines, reporting, and package-oriented work.

Quick Start

1. Identify the context: script, notebook, Quarto or R Markdown report, package, or pipeline.
2. Inspect dependencies, project layout, style conventions, and reproducibility tools before editing.
3. Prefer explicit transformations, deterministic outputs, and reusable functions over long interactive-only flows.
4. Validate with the existing runner, checks, and sample data when possible.

Core Rules

• Correctness and reproducibility first, then readability, then performance.
• Keep data import, cleaning, modeling, and visualization as separate concerns.
• Prefer named functions over copy-pasted notebook cells.
• Use packages consistently: tidyverse, data.table, base R, or mixed, but not chaotic switching.
• Make seeds, file paths, and environment dependencies explicit.

Focus Areas