Installation

1. 1
   Make sure Claude is on your device and in your terminal.

   Skills load from ~/.claude/skills/ when Claude Code starts up — so you need it on your machine first. If you don't have it yet, install it once with the command below, then run claude in any terminal to verify.

   One-time setup

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   npm i -g @anthropic-ai/claude-code

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2. 2
   Paste into Claude Code or into your terminal.

   Install

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   git clone ht••••••••••••••••••••••••••••••••••••••••••••••••••••• •••••••••••••••••••••••••••••••••••••• •• ••••• •• ••••••••••••••••••••••••••••••••••••••••••• •• •• •• •••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••• ••••••••••••••••••••••••••••••••••••••••••••

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   This copies the whole skill folder into ~/.claude/skills/academic-figure-joshua-zyy/ — the SKILL.md plus any scripts, reference docs, or templates the skill ships with. Safe default: works for every skill.

   Faster alternative (instruction-only skills)

   Skips the clone and grabs only the SKILL.md file. Don't use this if the skill ships Python scripts, reference markdowns, or asset templates — they won't be downloaded and the skill will fail when it tries to load them.

   Quick install (SKILL.md only)

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   mkdir -p ~/.•••••••••••••••••••••••••••••••••••••••• •• •••• ••••• •••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••• •• ••••••••••••••••••••••••••••••••••••••••••••••••••••

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3. 3
   Restart Claude Code.

   Quit and reopen Claude Code (or any other agent that loads from ~/.claude/skills/). New skills are picked up on startup.

4. 4
   Just ask Claude.

   Skills auto-activate when your request matches the skill's description — no slash command needed. Trigger phrases live in the skill's own frontmatter; you can read them in the “What this skill does” section above.

Prefer to read the source first? Open on GitHub.

When Claude uses it

Create, revise, or audit academic data/result figures for CS/AI/ML papers. Data/result plots default to Python-generated editable SVG with CS/AI/ML-specific design rules for benchmarks, ablations, training dynamics, robustness, diagnostics, distributions, confusion matrices, and efficiency tradeoffs. Use when: generating plots from experiment results or numeric data, auditing publication figures, suggesting data-driven figure types, revising chart colors/layouts/labels, or preparing figure QA reports. Model framework diagrams, architecture diagrams, overview diagrams, and complex mechanism schematics are outside this skill's automatic drawing scope; provide only manual figure requirements or caption/blueprint notes when needed. Triggers on: 绘图, figure, chart, 画图, 实验图, 训练曲线, 消融实验, 对比图, 混淆矩阵, 结果图, 性能图, 鲁棒性图, 效率图, plot, publication figure, 数据可视化, generate plot, figure blueprint, 建议图表类型, figure audit, 审查图表, figure revision, 修改图表.

What this skill does