Scientific Graphical Abstract Generator

AI-Powered Scientific Visualization Tool - Generate editable graphical abstracts for research papers

Description

Generate professional graphical abstracts for scientific papers using multiple AI models. This skill transforms research descriptions and data into publication-quality, editable SVG visualizations.

Features

• Multiple AI Models: Support for Claude, GPT-4o, DeepSeek, and other multimodal models
• Editable SVG Output: Generate vector graphics that can be edited in Inkscape, Illustrator, or any SVG editor
• Multiple Chart Types: Bar charts, line charts, pie charts, scatter plots, flowcharts, diagrams
• Data-Driven Visuals: Automatically create charts from CSV/JSON data
• Customizable Styles: Adjust colors, fonts, layouts to match journal requirements
• Publication Ready: High-quality output suitable for scientific journals

Usage

/graphical-abstract Generate a graphical abstract showing the research workflow for a CRISPR gene editing study
/graphical-abstract Create a bar chart comparing the performance of three different machine learning models from this data: [data]
/graphical-abstract Design a flowchart illustrating the mechanism of action of the proposed drug
/graphical-abstract Generate a line chart showing temperature changes over time from the following CSV data

Examples

Generate Research Workflow Diagram

/graphical-abstract Create a graphical abstract showing the workflow: Sample preparation → RNA extraction → Sequencing → Data analysis → Results visualization. Use a clean, professional style with blue color scheme.

Create Data Visualization

/graphical-abstract Generate a bar chart with the following data:
Model A: 85% accuracy
Model B: 92% accuracy
Model C: 78% accuracy

Title: Model Performance Comparison
Y-axis: Accuracy (%)
Color scheme: Professional blue gradient

Generate Mechanism Diagram

/graphical-abstract Design a schematic diagram showing how the proposed inhibitor binds to the active site of the enzyme, blocking substrate access. Include labels for key components.

Command Reference

generate

Generate a graphical abstract.

Option	Description
--prompt	Description of what to visualize
--data	Data file (CSV/JSON) for charts
--type	Chart type: bar, line, pie, scatter, flowchart, diagram
--model	AI model: claude, gpt4o, deepseek (default: claude)
--style	Style: minimal, professional, colorful, journal
--output	Output SVG file path
--width	Canvas width (default: 800)
--height	Canvas height (default: 600)

template

Use predefined templates for common visualizations.

Option	Description
--type	Template type: workflow, mechanism, comparison, timeline
--prompt	Specific requirements

Supported Models

Claude (Recommended)

• Best for: Complex diagrams, scientific illustrations
• Vision capabilities: Excellent
• API: Anthropic Claude API

GPT-4o

• Best for: Charts, data visualization
• Vision capabilities: Very good
• API: OpenAI API

DeepSeek

• Best for: Technical diagrams, cost-effective
• Vision capabilities: Good
• API: DeepSeek API

Output Format

All outputs are in SVG format which offers:

• Editable: Open in Inkscape, Adobe Illustrator, or any text editor
• Scalable: Infinite resolution without quality loss
• Web-ready: Can be embedded directly in websites
• Publication quality: Meets most journal requirements

Example SVG structure:

<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 800 600">
  <!-- Editable elements with clear structure -->
  <g id="chart-area">...</g>
  <g id="labels">...</g>
  <g id="legend">...</g>
</svg>

Notes

• For complex visualizations, provide detailed descriptions
• Data files should be in CSV or JSON format
• SVG files can be edited after generation
• Different models may produce different styles
• Journal-specific requirements can be specified in the prompt

Related Skills

• sci-data-extractor - Extract data from scientific papers
• semanticscholar-search-skill - Search academic papers
• pubmed-search-skill - Search biomedical literature