Claude Skill
aref-vc/tufte-claude-skill
一个Claude Code技能,将“给我画个图表”转化为符合塔夫特规范的图表。提炼自爱德华·塔夫特的三本奠基性著作,实现极简、数据丰富的可视化。
概览
仓库信息
安装这个 Skill
git clone https://github.com/aref-vc/tufte-claude-skill.git ~/.claude/skills/tufteRegistry 信息
项目简介
一个Claude Code技能,能将简单的图表请求转化为符合爱德华·塔夫特图形卓越原则的数据可视化图表,提炼自他的三本奠基性著作。
Claude Code skill that turns 'make me a chart' into a Tufte-compliant chart. Distilled from Edward Tufte's three foundational books.
要点
- 从自然语言提示生成符合塔夫特规范的图表
- 提炼自爱德华·塔夫特的三本奠基性著作
- 极简风格、数据墨水比优化的可视化
- 与Claude Code工作流无缝集成
使用场景
- 快速生成可用于报告的出版级图表
- 为演示创建清晰、无杂乱的数据可视化
- 借助塔夫特风格设计增强数据叙事
- 在保持高设计标准的同时自动化图表创建
README 摘要
# tufte-claude-skill A Claude Code skill that turns "make me a chart" into a Tufte-compliant chart. Distilled from the three foundational books by Edward R. Tufte. <table> <tr> <td align="center" width="33%"><img src="assets/vdqi-cover.svg" alt="The Visual Display of Quantitative Information" width="240"/></td> <td align="center" width="33%"><img src="assets/ei-cover.svg" alt="Envisioning Information" width="240"/></td> <td align="center" width="33%"><img src="assets/ve-cover.svg" alt="Visual Explanations" width="240"/></td> </tr> <tr> <td align="center"><b>The Visual Display of Quantitative Information</b><br/><i>1983 · 2nd ed. 2001</i><br/><sub>pictures of <b>numbers</b></sub></td> <td align="center"><b>Envisioning Information</b><br/><i>1990</i><br/><sub>pictures of <b>nouns</b></sub></td> <td align="center"><b>Visual Explanations</b><br/><i>1997</i><br/><sub>pictures of <b>verbs</b></sub></td> </tr> </table> --- ## Install Clone into your Claude Code skills directory: ```bash git clone https://github.com/aref-vc/tufte-claude-skill.git ~/.claude/skills/tufte ``` That's it. Claude Code auto-loads the skill on next launch. To verify, run `/tufte` or ask Claude to "make a chart of anything." To update later: ```bash cd ~/.claude/skills/tufte && git pull ``` To uninstall: ```bash rm -rf ~/.claude/skills/tufte ``` --- ## The three books, distilled Tufte gives the three-book taxonomy himself on page 9 of *Visual Explanations*: - **VDQI** — how to depict data and enforce statistical honesty. The book that gave us *data-ink ratio*, *chartjunk*, *lie factor*, *small multiples*. - **EI** — how to lay out information in space. Layering, micro/macro readings, color rules, escaping flatland. - **VE** — how to show motion, causality,
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