codex-visio-paper-figure-skill: 科研绘图skill、论文绘图skill、图片转visio等可编辑格式,将生成图转化为论文可编辑图,便于作者调整绘图细节

by pengjunchi0 · Codex Skill · ★ 680

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install codex-visio-paper-figure-skill

git clone https://github.com/pengjunchi0/codex-visio-paper-figure-skill.git "$env:USERPROFILE\.codex\skills\visio-image-rebuilder"

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 66/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

academic-figurescodexeditable-diagramsimage-to-visioscientific-figuresskillsvisio

Quick Facts

Stars680
Forks31
LanguagePowerShell
CategoryCodex Skill
LicenseMIT
Quality Score66/100
Open Issues1
Last Updated2026-07-28
Created2026-05-28
Platformscodex
Est. Tokens~8k

About codex-visio-paper-figure-skill

Codex 科研论文绘图 Skill 当前版本: 是一个面向科研论文配图工作流的 Codex Skill。它用于把参考图片、截图或生成图还原为 Microsoft Visio 原生可编辑图形,并从同一个 Visio 源文件导出 PNG、SVG、PDF、PPTX 等交付格式。 核心目标是让 Codex 通过 Visio 原生形状、文本、连线、分组和样式重建论文配图、模型框架图、流程图和多面板科学图。 注意! 主要适用于模型图、架构图、流程图等。其余场景如指标图(或含真实数据结果的)最好使用脚本或让 Agent 提取数据后用脚本绘图。 适用场景 适合: 根据 PNG/JPG/截图重建 Visio 图。 将 AI 生成的论文模型图转成可编辑 。 按参考图修改已有 Visio 文件的布局、配色、字体或模块结构。 对复杂多面板科学图进行结构化复刻。 检查 是否误用了整张参考图嵌入。 给 Visio...

Compatible Skills

These tools work well together with codex-visio-paper-figure-skill for enhanced workflows:

  • AgentFigureGallery — semantic(0.29)+complementary+rare_topics+similar_pop+shared_platform (50%)
  • paperbanana-skill — semantic(0.39)+complementary+rare_topics+similar_pop (48%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

View on GitHub → Browse Codex Skill tools