Scientific Visualization
Skill Verifiziert AktivMeta-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 clear, accurate, and accessible figures for scientific publications, ensuring compliance with journal standards and best practices.
Funktionen
- Orchestrates Matplotlib, Seaborn, and Plotly for figure generation
- Provides journal-specific style presets and export functions
- Includes colorblind-friendly palettes and accessibility guidelines
- Offers detailed examples for various plot types and statistical rigor
- Automates figure export in required formats (PDF, TIFF, PNG) and resolutions
Anwendungsfälle
- Creating figures for journal submission (Nature, Science, Cell, etc.)
- Ensuring figures are colorblind-friendly and accessible
- Making multi-panel figures with consistent styling
- Exporting figures at correct resolution and format (PDF, EPS, TIFF)
- Improving existing figures to meet publication standards
Nicht-Ziele
- Direct data analysis or statistical modeling (relies on external libraries)
- Generating figures for non-scientific contexts (e.g., marketing, general presentations)
- Providing a GUI-based plotting tool (operates via code and agent prompts)
Praktiken
- Data visualization
- Scientific communication
- Publication preparation
Voraussetzungen
- Python 3.11+ recommended
- Matplotlib, Seaborn, Plotly (installed by agent)
- uv (for dependency management)
Execution
- info:Pinned dependenciesWhile the project uses 'uv' for package management, explicit lockfiles or pinned versions for the core libraries (matplotlib, seaborn, plotly) are not directly evident in the skill's immediate files, though the overall repo may have them.
Installation
npx skills add K-Dense-AI/claude-scientific-skillsFührt das Vercel skills CLI (skills.sh) via npx aus — benötigt Node.js lokal und mindestens einen installierten skills-kompatiblen Agent (Claude Code, Cursor, Codex, …). Setzt voraus, dass das Repo dem agentskills.io-Format folgt.
Qualitätspunktzahl
VerifiziertVertrauenssignale
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