科研可视化工具

科研可视化工具 is a Data skill for Claude Code, published by XiaoMaColtAI in math-modeling-skill.

819 stars51 forkson XiaoMaColtAI/math-modeling-skillAdded 2026/08/23+8% in starsRepository updated 2026/08/22

claude-codeclaude-skillscodexcodex-skillcumcmdeepseek-harnessmath-modelingmcm-icmskillsvibe-coding

Install in seconds

Install 科研可视化工具

Copy 科研可视化工具 into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/XiaoMaColtAI/math-modeling-skill/tree/main/tools/figure ~/.claude/skills/figure

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/XiaoMaColtAI/math-modeling-skill.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

科研可视化工具从数据剖析到出版级成图，先做 EDA、选图决策和错误拦截，再进行绘制、自检与多格式导出。适合论文配图、科研数据可视化和数学建模结果图制作。

科研可视化工具 is cataloged under Data on DirSkills. 科研可视化工具 comes from a repository tagged claude-code, claude-skills, codex, codex-skill and cumcm.

Documentation

Excerpt

从数据剖析到出版级成图 | Python + MATLAB | 自检 + AI 读图闭环

SKILL_ROOT：math-modeling-skill 仓库根目录（只读）。
本文件中所有 tools/figure/... 路径均相对于 SKILL_ROOT。
CLI 命令使用 "<SKILL_ROOT>/tools/figure/scripts/..." 格式，确保从任何工作目录均可执行。
Python import 使用 sys.path.insert(0, os.path.join(SKILL_ROOT, 'tools', 'figure', 'scripts')) 后导入。

本工具融合 nature-figure 的图表契约/后端路由架构与 scipilot-figure-skill 的数据剖析/选图决策/自检闭环，并扩展数学建模特有的三类图体系和子问题覆盖检查。永远先思考再画：

只覆盖纯数据图：折线、柱状、散点、箱线/小提琴、热力图、误差棒、分布图、相关性矩阵、雷达图、 3D 曲面、多面板组合。不做示意图、流程图、架构图。

python "<SKILL_ROOT>/tools/figure/scripts/profile_data.py" data.csv --group group --group condition

This is the opening of the README. Read the full README on GitHub.

What else does XiaoMaColtAI publish alongside 科研可视化工具?
科研可视化工具 is one of 10 skills that DirSkills catalogs from XiaoMaColtAI/math-modeling-skill, the repository it ships in. Its siblings there include DOCX Tools, Excel Tools and LaTeX工具. Each one is a separate skill with its own page in this directory, installs the same way 科研可视化工具 does, and is maintained by XiaoMaColtAI in that same repository. The rest of the collection is listed on the XiaoMaColtAI/math-modeling-skill page.
How does 科研可视化工具 compare to other Data skills?
科研可视化工具 ranks #503 by stars among the 668 Data skills in this catalog. The most-starred ones next to it are Benchmark Methodology, Jupyter Notebook and Solana. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of 科研可视化工具 against them. Open each page to compare what they document and how they install.