Create or review academic figures in three modes. journal-spec creates or reviews publication-ready figures for journal submission specs using matplotlib, seaborn, plotly, or industrytslib. from-data fills a named paper-style catalog with user data. from-image reproduces an uploaded paper figure as a matplotlib script and 300 dpi PNG. Use for 论文配图, 期刊图, 科研绘图, 审阅投稿图, 用某论文风格画数据, 复现这张图, or a named catalog style. An explicit journal target takes precedence over a style or reference image. Paper reading and multi-paper synthesis route to their dedicated research skills.
How to install academic-figure?
bahayonghang/my-claude-code-settings/academic-figure
$npx -y skills add bahayonghang/my-claude-code-settings --skill academic-figureInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/bahayonghang/my-claude-code-settings" --skill "bahayonghang/my-claude-code-settings/academic-figure"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/bahayonghang/my-claude-code-settings" that are relevant to the current task. Run `npx skills add "https://github.com/bahayonghang/my-claude-code-settings"` and select the relevant skills, then follow their instructions.
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