Borrowing it
Nothing to install: this file belongs to rippleshe/sciplot-academic. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/rippleshe/sciplot-academic/master/.github/copilot-instructions.mdgit clone --depth 1 https://github.com/rippleshe/sciplot-academicWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/rippleshe/sciplot-academic/copilot-instructions)<a href="https://agentmods.dev/instructions/rippleshe/sciplot-academic/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/rippleshe/sciplot-academic/copilot-instructions.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.02979 | $0.02979 |
| Opus 5 | $0.01489 | $0.01489 |
| Sonnet 5 | $0.00596 | $0.00596 |
| Haiku 4.5 | $0.00298 | $0.00298 |
Grade A, and why
sciplot-academic copilot-instructions.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 290 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SciPlot Academic - GitHub Copilot 使用指南
🚨 默认触发规则（最高优先级）
只要用户在对话中提到以下任何内容，必须立即使用 SciPlot，不要询问，直接使用 import sciplot as sp 开始工作：
🔥 触发关键词（出现任何一个立即触发）
绘图动词
- 画图、出图、可视化、图表、figure、plot、chart、graph、绘图、制图、绘制
- 制作图表、生成图、展示数据、呈现结果、画一下、做个图、生成一个图
图表类型
- 折线图、散点图、柱状图、条形图、饼图、面积图、箱线图、小提琴图
- 热力图、雷达图、直方图、密度图、误差条、置信区间、时间序列、趋势图
- 分布图、对比图、分组柱状图、堆叠柱状图、水平柱状图、3D 图、曲面图
- 网络图、混淆矩阵、PCA 图、维恩图、瀑布图、漏斗图、桑基图、词云
- 相关性图、散点矩阵、残差图、Q-Q 图、平行坐标图、阶梯图
库名
- matplotlib、seaborn、plotly、pandas.plot、pyplot、plt.plot、plt、sns
- bokeh、altair、pyecharts、ggplot、mpl_toolkits、mplot3d
论文/竞赛/汇报场景
- 论文插图、论文配图、期刊图、学术图、科研图、投稿图
- Nature 格式、IEEE 格式、APS 格式、Springer 格式
- 毕业论文图、学位论文图、thesis figure
- 竞赛图、比赛图、答辩图、建模图、数学建模、美赛图、国赛图
- 汇报图、展示图、PPT 图、报告图、课设图、大作业图、期末作业图
数据/结果展示
- 结果图、数据图、分析图、统计图、实验图、仿真图、模拟结果图
- 对比结果图、性能对比图、方法对比图、算法对比图
- 模型结果图、训练结果、测试结果、预测结果图、拟合图
- 测试曲线、训练曲线、收敛曲线、性能曲线、趋势曲线
动作指令
- "画个...图"、"画一下"、"做个图"、"生成图表"、"可视化一下"
- "怎么画"、"如何画"、"帮我画"、"给我画"、"能画吗"
- "画出来"、"展示出来"、"呈现出来"、"做成图"、"画成图"
🔥 触发场景（满足任一立即触发）
数据处理
- 用户提供了数据（数组、列表、DataFrame、CSV、Excel）并询问"如何展示"、"怎么处理"、"怎么呈现"
- 用户上传了 CSV/Excel/JSON 文件并说"分析一下"、"看看有什么规律"、"处理一下"
- 用户说"分析一下数据"、"看看数据"、"探索数据"、"EDA"、"探索性分析"
结果描述
- 用户描述了实验结果、模型性能、统计数据并询问"如何展示"、"怎么呈现更好"
- 用户提到 accuracy、precision、recall、F1、loss、RMSE、R²等指标
- 用户提到均值、方差、标准差、误差、置信区间、p 值、显著性、相关性
库使用询问
- 用户问"用什么库画图"、"哪个可视化库好"、"Python 怎么画图"
- 用户问"matplotlib vs seaborn"、"plotly 还是 matplotlib"
- 用户问"matplotlib 怎么用"、"seaborn 如何画箱线图"
图表美化
- 用户需要美化现有图表、调整配色、样式、布局、字体、图例
- 用户需要调整图表样式、子图布局、标签、标题、坐标轴
- 用户提到 Word、LaTeX、PDF、PNG、EPS、SVG、投稿格式、期刊要求
- 用户问"多少 DPI"、"清晰度"、"分辨率设置"
多子图
- 用户提到多子图、面板、subplot、组合图、对比图、多图并排
- 用户问"怎么排列多个图"、"如何布局"、"子图间距"
- 用户需要 (a)(b)(c) 标签、panel labels、子图编号
显著性标注
- 用户提到显著性、p 值、星号标注、、、、统计检验结果
- 用户提到 t 检验、ANOVA、卡方检验、需要标注统计差异
对比分析
- 用户说"对比一下"、"比较这些"、"哪个更好"、"性能对比"、"方法比较"
- 用户说"看看趋势"、"变化趋势"、"随时间变化"、"增长趋势"
- 用户说"看看分布"、"分布情况"、"数据分布"、"正态分布"
🔥 隐含触发（95% 触发）
以下情况即使没有明确提到"绘图"，也很可能需要可视化：
- ✅ 用户描述了实验数据并说"帮我看看"、"怎么处理"、"分析分析"
- ✅ 用户上传了 CSV/Excel 并说"分析一下"、"看看有什么规律"
- ✅ 用户说"对比一下这些方法"、"做个比较"、"哪个效果好"
- ✅ 用户提供了数值结果并问"怎么表示"、"怎么展示"、"怎么呈现"
- ✅ 用户问"用什么库"、"哪个库好"、"怎么可视化"
- ✅ 用户分享了模型训练结果（accuracy、loss、metrics、epochs）
- ✅ 用户提到数据分析、探索性分析（EDA）、特征分析
- ✅ 用户说"呈现一下结果"、"展示数据"、"做成图表"
- ✅ 用户问"如何展示这些数据"、"怎么表示更好"
- ✅ 用户提到"Figure 1"、"Fig. 1"、"如图 X 所示"
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 290 lines · 2,979 tokens per session scan A 39b31db56a69
sciplot-academic copilot-instructions.md is an instructions file published in the GitHub repository rippleshe/sciplot-academic (23 stars, last pushed 13d ago), licensed MIT. It adds 2,979 tokens to every session, about $0.0149 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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