Academic Figure Generator is a local web application that analyzes uploaded academic papers and generates prompts and research figures with AI. Researchers use it to turn papers into downloadable diagrams through a workflow for uploading, reviewing, generating, and editing images. The catalogue skills provide this figure-generation workflow for coding agents.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add LigphiDonk/academic-figure-generator --skill academic-figure-promptgit clone --depth 1 https://github.com/LigphiDonk/academic-figure-generatorWrote 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/skills/ligphidonk/academic-figure-generator/academic-figure-prompt)<a href="https://agentmods.dev/skills/ligphidonk/academic-figure-generator/academic-figure-prompt"><img src="https://agentmods.dev/badge/skills/ligphidonk/academic-figure-generator/academic-figure-prompt/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ligphidonk/academic-figure-generator/academic-figure-prompt"><img src="https://agentmods.dev/badge/skills/ligphidonk/academic-figure-generator/academic-figure-prompt.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high YARA Match · line 5 YARA rule matched a hack tool or exploit indicator (offensive tools, reconnaissance, privilege escalation, or exploit frameworks).Fix: Remove offensive tool references and exploit code. Legitimate agent skills should not contain penetration testing tools, exploit frameworks, or reconnaissance utilities.
- high Prompt Injection · line 377 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
- high Prompt Injection · line 379 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
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 | $0.00186 | $0.05421 |
| Opus 5 | $0.00093 | $0.02710 |
| Sonnet 5 | $0.00037 | $0.01084 |
| Haiku 4.5 | $0.00019 | $0.00542 |
Grade A, and why
Academic Figure Prompt 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 13d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- Academic Figure Prompt — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 391 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Academic Figure Prompt — 学术论文配图提示词生成器
为学术论文生成极其详细的英文提示词，供 AI 图片生成工具（NanoBanana / Gemini / Midjourney / DALL-E）生成顶会级别的专业学术配图。
核心理念
生成的提示词必须做到三点：信息密度极高、视觉风格精确、内容完整无遗漏。
宁可提示词过长过详细，也绝不能简化省略。学术配图的价值在于精准传达复杂信息，而非美观简洁。
工作流程
Step 1: 理解论文内容
在生成提示词之前，必须先充分理解论文内容：
- 阅读用户提供的论文/章节源文件（LaTeX、Word、PDF 等）
- 提取每个章节的核心概念、方法、模型架构、数据流
- 识别所有需要配图的位置及其内容需求
- 理解论文中的数学符号、变量含义、维度信息
Step 2: 分析参考图（如有）
如果用户提供了参考图，必须详细分析：
| 分析维度 | 提取内容 |
|---|---|
| 配色方案 | 主色、辅色、强调色的精确色值（如 #3A8F85） |
| 布局结构 | 流向（左→右 / 上→下）、分区方式、层次关系 |
| 模块样式 | 框的形状、边框粗细、填充色、圆角大小 |
| 标注方式 | 标题栏样式、公式标注、维度标注、箭头类型 |
| 信息密度 | 每个模块内的子细节数量、嵌入缩略图的使用方式 |
| 特殊元素 | 反馈环路、虚线框、跳接箭头、图例位置 |
Step 2.5: 配色方案选择（必须在生成提示词前完成）
在生成任何提示词之前，必须先向用户展示配色选项并等待确认。
展示以下内容：
请选择配色方案（输入编号或自定义）：
| # | 方案名 | 风格定位 | 主色 | 辅色 | 点缀色 |
|---|---|---|---|---|---|
| A | Okabe-Ito 学术标准 | Nature / Science / CVPR 推荐，色盲友好 | Steel Blue #0072B2 |
Warm Orange #E69F00 |
Bluish Green #009E73 |
| B | Blue 单色系 | 克制、模块详解图适用 | Navy #0072B2 |
Medium Blue #4A90D9 |
Light Blue #A0C4E8 |
| C | Teal + Amber | 现代感强，ICLR / NeurIPS 风 | Deep Teal #00897B |
Amber #FFB300 |
Soft Grey #ECEFF1 |
| D | Navy + Coral | 沉稳大气，IEEE 期刊风 | Deep Navy #1A3A5C |
Coral #E05A47 |
Warm Sand #F5ECD7 |
| E | Slate + Violet | 优雅冷调，医学 / 生物信息学风 | Slate Blue #3F51B5 |
Muted Violet #7E57C2 |
Pale Lavender #EDE7F6 |
| F | Forest + Gold | 厚重学术感，自然科学期刊风 | Forest Green #2E7D32 |
Gold #C49A00 |
Cream #F9F6EE |
| G | Minimal Grey | 极简灰度 + 单一强调色，arXiv 技术报告风 | Charcoal #263238 |
Steel #546E7A |
单一强调（用户指定） |
| H | 自定义 | 由用户提供色值或从下方工具选取 | — | — | — |
如需自定义配色，推荐以下工具：
- Coolors — 随机生成 + 锁定调整，导出色板：https://coolors.co
- ColorHunt — 精选高质量色板，支持标签筛选：https://colorhunt.co
- Adobe Color — 色轮 + 互补/类比/三分配色生成：https://color.adobe.com/create
- ColorBrewer — 专为学术数据可视化设计，支持色盲安全验证：https://colorbrewer2.org
- Viz Palette — 专为数据可视化配色，实时模拟色盲效果：https://projects.susielu.com/viz-palette
- Paletton — 色相环驱动配色方案设计器：https://paletton.com
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.
- 13d ago First seen · 391 lines · 186 tokens per session scan A 5f7f71a77fa4
Academic Figure Prompt is a skill published in the GitHub repository LigphiDonk/academic-figure-generator (2,309 stars, last pushed 5mo ago), licensed MIT. It adds 186 tokens to every session and 5,421 once invoked, about $0.0009 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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