This repository is a modular toolkit for academic research workflows, providing reusable 'skills' that assist with tasks such as manuscript preparation, figure generation, citation management, paper downloading, and presentation creation. Each skill is self-contained with its own workflow, documentation, and validation, while sharing common components through a nature-shared module. The system is designed for integration with AI agents (like Codex and Claude Code) and emphasizes verifiable, reproducible outputs that comply with journal-specific standards (particularly Nature Portfolio journals).
This repository is a comprehensive collection of examples for the **knitr** R package, demonstrating features such as chunk options, hooks, multiple language engines (Python, Bash, C++, etc.), caching, child documents, and output formats (Markdown, LaTeX, HTML, reST, etc.). It serves as both a tutorial for new users and an integration test suite for the knitr package itself. The examples are self-contained, using built-in R datasets (e.g., iris, mtcars, cars) and simple computational tasks. While not a production application or data pipeline, the repo provides a valuable reference for literate programming and reproducible research with R. It is actively maintained by the knitr author and community.