Yuan1z0825/nature-skills

What it solves

nature-skills provides a library of reusable, standardized research skills designed to help AI scholars automate complex academic workflows. It bridges the gap between raw AI capabilities and the rigorous requirements of high-impact journals (like Nature), automating tasks such as paper reading, manuscript polishing, peer review simulation, and figure generation.

How it works

The project is organized as a collection of skill packages, each centered around a SKILL.md file that defines specific rules and workflows. These skills are designed to be ingested by AI agents (such as Codex, Claude Code, or other agentic frameworks) which then execute the instructions to perform research tasks. The system uses a modular structure where individual skills can be installed globally or per-project, often relying on a shared support package (nature-shared) for common references.

Who it’s for

It is primarily for AI researchers and global scholars who want to transition to an "agentic" research paradigm, allowing them to use AI agents to control their local environment and automate the production of high-quality academic outputs.

Highlights

• Comprehensive Academic Suite: Includes skills for reading papers (Markdown readers), polishing text to Nature style, simulating blind reviewer reports, and generating publication-ready figures.
• Agent-Native Design: Specifically built to be understood and executed by AI agents, allowing the agent to learn the design philosophy directly from the repository.
• Broad Integration: Supports installation via npx skills and provides dedicated integration paths for Claude Code and Codex.
• Research-to-Patent Pipeline: Includes a specialized skill to convert academic papers into Chinese invention patent drafts.
• Automated Literature Pipeline: Features a system for multi-source literature discovery, scoring, and local archiving.