Individual skill
scipilot-figure-skill
SciPilot Skills 家族成员,负责科研数据可视化——但定位不是"画图工具", 而是"可视化顾问"。先做数据剖析(列类型/样本量/分布/异常值/分组结构/相关性), 再结合用户的论证目标推荐图型,主动拦截科研画图的经典错误(小样本画均值柱掩盖 分布、双 Y 轴、饼图、Y 轴不当截断、rainbow 色图、把分类点连成折线等),最后 产出 Nature / Science / IEEE / Elsevier / PNAS / 中文核心期刊级别的成图。 覆盖纯数据图:折线、柱状、散点、箱线 / 小提琴、热力图、误差棒、分布图(直方 图 / KDE)、相关性矩阵 / 散点矩阵、多面板组合。技术栈 matplotlib + seaborn + SciencePlots(静态)+ plotly(交互)。中英文双语,中文模式自动配置 Noto Sans CJK / Source Han Sans / SimHei 并修复负号方框,支持中文期刊"宋体正文 + Times New Roman 数字"混排。默认色盲安全配色 + 冗余编码 + 灰度预览。出图后做 "视觉自检闭环":渲染 PNG 预览→程序自检缺字/文字裁切/刻度重叠→AI 读图复核遮盖 与子图对齐→回改重渲,直到通过。 当用户的任务涉及以下任何情况时主动触发:论文配图、科研画图、数据可视化、 不知道用什么图、怎么展示数据、用什么图好、期刊投稿图、figure、出版级图表、 matplotlib、seaborn、plotly、误差棒、显著性标注、色盲安全配色、矢量图导出、 中文论文图表、多面板。**即使用户只是给一批数据问"这个怎么画"或"用什么图 好",也应使用本技能——本技能首要能力是"判断该用什么图",其次才是绘制。** 不做示意图、流程图、架构图。
SKILL.md
Source commit 43098ddb9e6a6d142218540c114f9ed38922fc42
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- No
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Not checked yet
- Last checked
- Nov 9, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
Install this skill
Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.
An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.
Repository context
- Repository stars (not skill ratings)
- 2,817
- Repository last updated
- Jun 15, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- engineering Derived category
Files and excerpt
File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.
Browse files
.gitignoreasset · 513 bytesLICENSEasset · 1,063 bytesREADME.mddoc · 14,453 bytesSKILL.mdcore · 17,171 bytesSKILL.mdcore · 17,171 bytesSKILL.mdcore · 17,171 bytesSKILL.mdcore · 17,171 bytesreferences/chart_selection.mddoc · 11,584 bytesreferences/data_profiling.mddoc · 8,566 bytesreferences/journal_specs.mddoc · 7,428 bytesreferences/plot_recipes.mddoc · 19,204 bytesreferences/publication_checklist.mddoc · 5,993 bytesreferences/visual_review.mddoc · 7,330 bytesreferences/viz_pitfalls.mddoc · 15,851 bytesrequirements.txtdoc · 287 bytesscripts/check_figure.pyruns · 9,709 bytesscripts/export_figure.pyruns · 6,450 bytesscripts/layout_tools.pyruns · 9,351 bytesscripts/profile_data.pyruns · 17,764 bytesscripts/setup_style.pyruns · 11,794 bytesscripts/visual_qa.pyruns · 12,677 bytes
Read excerpt
# scipilot-figure-skill — 科研数据可视化顾问
> SciPilot Skills 家族成员 | 从数据剖析到出版级成图
## 概述
科研工作者最大的画图痛点往往不是"不会用 matplotlib",而是"手上一堆数据,不知道该用什么图把结论讲清楚"。本技能的**首要能力是【思考与判断】**,其次才是【绘制】。
具体地——**永远先思考再画**:
1. 先理解数据再选图——拿到数据先做 EDA,用事实驱动图型选择
2. 先想清楚"这张图要论证什么"——同样数据,不同论点 = 不同图
3. 主动拦截科研画图的经典错误,而不是顺从
4. 维度太多就建议拆图,不硬塞