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nature-skills Deep Dive: How a Shanghai Jiao Tong PhD Student Turned Nature Paper Writing into Replicable AI Skills

Forum topic · 小凯 · 2026-05-28

Summary

nature-skills is an open-source project by Yuan Yizhe, a medical AI PhD student at Shanghai Jiao Tong University, that packages the full workflow of writing Nature-level papers into 9 installable AI skills. The pipeline covers language polishing (nature-polishing), argument-driven drafting (nature-writing), publication-grade figures with matplotlib/ggplot2 (nature-figure), citation management (nature-citation), data availability statements (nature-data), bilingual paper reading (nature-reader), point-by-point peer-review responses (nature-response), paper-to-Chinese-PPT conversion (nature-paper2ppt), and parallel PubMed/CrossRef/arXiv search (nature-academic-search). Key design principles include a six-layer diagnostic before sentence-level polishing, 30-word sentence limits, calibrated hedging, figure contracts written before plotting, evidence-first writing order, and an explicit red/yellow/green traffic-light policy for what AI should never do. Only two skills are currently Stable; the rest are Beta/Draft. The project installs via Claude Code or Codex Desktop plugin marketplaces and is extensible with planned skills for statistics, methods, cover letters, and reviews.

nature-skills is an open-source project by Yuan Yizhe, a medical AI PhD student at Shanghai Jiao Tong University, that packages the full workflow of writing Nature-level papers into 9 installable AI skills. The pipeline covers language polishing (nature-polishing), argument-driven drafting (nature-writing), publication-grade figures with matplotlib/ggplot2 (nature-figure), citation management (nature-citation), data availability statements (nature-data), bilingual paper reading (nature-reader), point-by-point peer-review responses (nature-response), paper-to-Chinese-PPT conversion (nature-paper2ppt), and parallel PubMed/CrossRef/arXiv search (nature-academic-search). Key design principles include a six-layer diagnostic before sentence-level polishing, 30-word sentence limits, calibrated hedging, figure contracts written before plotting, evidence-first writing order, and an explicit red/yellow/green traffic-light policy for what AI should never do. Only two skills are currently Stable; the rest are Beta/Draft. The project installs via Claude Code or Codex Desktop plugin marketplaces and is extensible with planned skills for statistics, methods, cover letters, and reviews.

Tags

#ai-writing#academic-writing#open-source#claude-code#scientific-figures#paper-polishing#peer-review#nature-journal

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