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qinyan-nature-figures

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面向 Nature Portfolio 与高影响力期刊的证据驱动科研绘图技能。用于从原始或汇总数据设计单图与多面板 figure、选择合适图形语法、编写 Python/R 绘图代码、重绘现有图件、生成机制示意图草案、撰写图注并导出可编辑 SVG/PDF 与高分辨率 TIFF/PNG；同时检查数据完整性、颜色可访问性、统计标注和最终尺寸可读性。触发场景包括 Nature 绘图、科研作图、论文配图、scientific figure、publication plot、multi-panel figure、graphical abstract、机制图、图形摘要和 figure audit。

skills/沁言学术skills/qinyan-nature-figures/SKILL.md

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# 沁言 Nature 科研绘图

先定义图要证明什么，再决定画什么。期刊级图件是证据结构、视觉层级、数据诚信和可复现导出的共同产物。

## 路由

- **定量图件**：使用 Python（matplotlib/seaborn）或 R（ggplot2/patchwork/ComplexHeatmap）。
- **机制图或图形摘要**：先建立概念与关系清单，再使用矢量工具或可用的图像生成能力制作草案；不得用 AI 图替代定量证据。
- **已有图件审查**：同时检查图源代码、最终导出和最终版面尺寸，不能只看屏幕截图。

优先服从用户现有语言与项目栈。用户未指定且不存在项目约束时，默认使用 Python，并在交付中说明；只有选择会显著影响复现或协作时才询问。

## 图件契约
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