# Ggterm Publish
> 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.
- Skill: `majiayu000/ggterm-publish` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add majiayu000/ggterm-publish`
- Raw SKILL.md: https://api.skillmd.com/api/skills/majiayu000/ggterm-publish/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Web & Frontend
- Author: majiayu000 (https://skillmd.com/u/majiayu000)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/majiayu000/ggterm-publish
---
# 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'
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