How do I install the Ggterm Publish skill?

Run npx skillmds@latest add majiayu000/ggterm-publish in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Ggterm Publish safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: makes network calls. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Ggterm Publish?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Ggterm Publish free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Ggterm Publish?

majiayu000 (@majiayu000) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Ggterm Publish by majiayu000 — Agent Skill

Name: Ggterm Publish
Rating: 4.666666666666667 (3 reviews)
Author: majiayu000

File contents

Publication Export with ggterm

Export terminal plots to publication-quality formats using Vega-Lite.

Prerequisites

The Vega-Lite CLI tools must be installed:

npm install -g vega-lite vega-cli canvas

How It Works

When a plot is created with the CLI, ggterm saves:

.ggterm/last-plot.json - The PlotSpec (ggterm format)
.ggterm/last-plot-vegalite.json - The Vega-Lite spec

Export Commands

To PNG (Raster)

npx vl2png .ggterm/last-plot-vegalite.json > plot.png

To SVG (Vector)

npx vl2svg .ggterm/last-plot-vegalite.json > plot.svg

To PDF

npx vl2pdf .ggterm/last-plot-vegalite.json > plot.pdf

To HTML (Interactive)

cat > plot.html << 'EOF'
<!DOCTYPE html>
<html>
<head>
  <script src="https://cdn.jsdelivr.net/npm/vega@5"></script>
  <script src="https://cdn.jsdelivr.net/npm/vega-lite@5"></script>
  <script src="https://cdn.jsdelivr.net/npm/vega-embed@6"></script>
</head>
<body>
  <div id="vis"></div>
  <script>
    const spec = SPEC_PLACEHOLDER;
    vegaEmbed('#vis', spec);
  </script>
</body>
</html>
EOF

# Replace placeholder with actual spec
bun -e "
const spec = require('./.ggterm/last-plot-vegalite.json');
const html = require('fs').readFileSync('plot.html', 'utf-8');
const result = html.replace('SPEC_PLACEHOLDER', JSON.stringify(spec, null, 2));
require('fs').writeFileSync('plot.html', result);
"

Custom Dimensions

To export with different dimensions, modify the Vega-Lite spec first:

bun -e "
const spec = require('./.ggterm/last-plot-vegalite.json');
spec.width = 800;
spec.height = 600;
require('fs').writeFileSync('.ggterm/last-plot-vegalite.json', JSON.stringify(spec, null, 2));
"
npx vl2png .ggterm/last-plot-vegalite.json > plot-large.png

Workflow

User creates a terminal plot using /ggterm-plot
User asks to export it for publication
This skill exports to the requested format

Troubleshooting

If vl2png/vl2svg fail, ensure dependencies are installed:

npm install -g vega-lite vega-cli canvas

On macOS, canvas may require additional setup:

brew install pkg-config cairo pango libpng jpeg giflib librsvg
npm install -g canvas --build-from-source

$ARGUMENTS

---name: ggterm-publishdescription: Export terminal plots to publication-quality formats (PNG, SVG, PDF, HTML). Use when the user wants to save, export, publish, or create a high-quality version of a plot.--- # Publication Export with ggterm Export terminal plots to publication-quality formats using Vega-Lite. ## Prerequisites The Vega-Lite CLI tools must be installed: ```bash npm install -g vega-lite vega-cli canvas ``` ## How It Works When a plot is created with the CLI, ggterm saves: - `.ggterm/last-plot.json` - The PlotSpec (ggterm format) - `.ggterm/last-plot-vegalite.json` - The Vega-Lite spec ## Export Commands ### To PNG (Raster) ```bash npx vl2png .ggterm/last-plot-vegalite.json > plot.png ``` ### To SVG (Vector) ```bash npx vl2svg .ggterm/last-plot-vegalite.json > plot.svg ``` ### To PDF ```bash npx vl2pdf .ggterm/last-plot-vegalite.json > plot.pdf ``` ### To HTML (Interactive) ```bash cat > plot.html << 'EOF' <!DOCTYPE html> <html> <head> <script src="https://cdn.jsdelivr.net/npm/vega@5"></script> <script src="https://cdn.jsdelivr.net/npm/vega-lite@5"></script> <script src="https://cdn.jsdelivr.net/npm/vega-embed@6"></script> </head> <body> <div id="vis"></div> <script> const spec = SPEC_PLACEHOLDER; vegaEmbed('#vis', spec); </script> </body> </html> EOF # Replace placeholder with actual spec bun -e " const spec = require('./.ggterm/last-plot-vegalite.json'); const html = require('fs').readFileSync('plot.html', 'utf-8'); const result = html.replace('SPEC_PLACEHOLDER', JSON.stringify(spec, null, 2)); require('fs').writeFileSync('plot.html', result); " ``` ## Custom Dimensions To export with different dimensions, modify the Vega-Lite spec first: ```bash bun -e " const spec = require('./.ggterm/last-plot-vegalite.json'); spec.width = 800; spec.height = 600; require('fs').writeFileSync('.ggterm/last-plot-vegalite.json', JSON.stringify(spec, null, 2)); " npx vl2png .ggterm/last-plot-vegalite.json > plot-large.png ``` ## Workflow 1. User creates a terminal plot using `/ggterm-plot` 2. User asks to export it for publication 3. This skill exports to the requested format ## Troubleshooting If vl2png/vl2svg fail, ensure dependencies are installed: ```bash npm install -g vega-lite vega-cli canvas ``` On macOS, canvas may require additional setup: ```bash brew install pkg-config cairo pango libpng jpeg giflib librsvg npm install -g canvas --build-from-source ``` $ARGUMENTS

Frequently asked questions

Ggterm Publish