AlterLab Scientific Viz
Skill ActivePart of the AlterLab Academic Skills suite. Meta-skill for publication-ready figures. Use when creating journal submission figures requiring multi-panel layouts, significance annotations, error bars, colorblind-safe palettes, and specific journal formatting (Nature, Science, Cell). Orchestrates matplotlib/seaborn/plotly with publication styles. For quick exploration use seaborn or plotly directly.
To empower researchers to create professional, accessible, and journal-compliant figures for scientific publications, streamlining the visualization process.
Features
- Orchestrates Matplotlib, Seaborn, and Plotly
- Applies publication styles for top journals
- Generates colorblind-safe palettes
- Exports figures in various publication formats (PDF, EPS, TIFF, PNG)
- Provides guidance on figure dimensions, resolution, and typography
Use Cases
- Creating figures for journal submissions (Nature, Science, Cell)
- Ensuring figures are colorblind-friendly and accessible
- Preparing multi-panel figures with consistent styling
- Exporting figures at correct resolution and format
Non-Goals
- Performing complex statistical analysis beyond plotting summary statistics
- Replacing direct use of plotting libraries for exploratory analysis
- Handling data cleaning or preparation
- Generating figures for non-academic purposes
Practices
- Scientific Visualization
- Data Visualization Best Practices
- Publication Standards
Prerequisites
- Python environment
- Matplotlib, Seaborn, Plotly, NumPy installed
Trust
- warning:Issues AttentionThere are 2 issues opened and 0 closed in the last 90 days, indicating slow maintainer engagement for recent issues.
Installation
npx skills add AlterLab-IEU/AlterLab-Academic-SkillsRuns the Vercel skills CLI (skills.sh) via npx — needs Node.js locally and at least one installed skills-compatible agent (Claude Code, Cursor, Codex, …). Assumes the repo follows the agentskills.io format.
Quality Score
Trust Signals
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