init-r-workspace

Create a standardized R analysis workspace with optional renv setup.

6|Updated Apr 8, 2026
One-click install
npx skills add https://github.com/blankuzr/R-Skills --skill init-r-workspace
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: init-r-workspace
Source: https://github.com/blankuzr/R-Skills/tree/main/gpt/skills/init-r-workspace
Command: npx skills add https://github.com/blankuzr/R-Skills --skill init-r-workspace

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Bootstrap a consistent local R analysis workspace by creating a standard project scaffold (main.R, src/, test/, data/, .here, LOG.md, and a local .codex/skills) with optional renv support, enabling reproducible analyses from a clean slate.

Core Features & Use Cases

  • Standard scaffold: main.R, src/, test/, data/, .here, LOG.md, and optional renv setup for reproducibility.
  • Reproducible environment: guidance to initialize and snapshot with renv to lock dependencies across machines.
  • Safe bootstrap: preserves existing files and reports what was created vs. already present.

Quick Start

Begin by initializing a new R project to generate the standard workspace scaffold and optional renv layer.

Frequently Asked Questions about init-r-workspace

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I set up a reproducible R project workspace with a standard directory structure?

A standardized R project workspace is created by automatically generating a scaffold with main.R, src/, test/, data/, and .here, ensuring a consistent and clean structural baseline for new reproducible analyses.

How do I initialize renv in a new R analysis project?

You can initialize renv in a new R analysis project through the optional renv integration provided during the workspace bootstrap, which guides dependency initialization and snapshotting to lock environments across machines.

What is the best way to structure R analysis projects across teams?

Structuring R analysis projects across teams is best handled by applying a deterministic scaffold that enforces consistent directories like src/ and test/ alongside a main.R entry point, ensuring uniform project setup and reproducibility.

Will bootstrapping an R workspace overwrite my existing project files?

Bootstrapping an R workspace will not overwrite your existing project files, as the process safely preserves current content and only reports what was newly created versus what was already present.

Do I need renv to create an R project scaffold?

You do not need renv to create an R project scaffold, as the renv setup is an optional layer; the Skill generates the core directory structure and main.R independently before integrating reproducibility features.