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graphical-abstract-wizard

Generate graphical abstract layout recommendations based on paper abstracts

skill-install โ€” Terminal

Install via CLI (Recommended)

clawhub install openclaw/skills/skills/aipoch-ai/graphical-abstract-wizard
Or

Graphical Abstract Wizard

This Skill analyzes academic paper abstracts and generates graphical abstract layout recommendations, including element suggestions, visual arrangements, and AI art prompts for Midjourney and DALL-E.

Usage

python scripts/main.py --abstract "Your paper abstract text here"

Or from stdin:

cat abstract.txt | python scripts/main.py

Parameters

ParameterTypeRequiredDescription
--abstract / -astringYes*The paper abstract text to analyze
--style / -sstringNoVisual style preference (scientific/minimal/colorful/sketch)
--format / -fstringNoOutput format (json/markdown/text), default: markdown
--output / -ostringNoOutput file path (default: stdout)

*Required if not providing input via stdin

Examples

Example 1: Basic Usage

python scripts/main.py -a "We propose a novel deep learning approach for protein structure prediction that combines transformer architectures with geometric constraints. Our method achieves state-of-the-art accuracy on CASP14 benchmarks."

Example 2: With Style Preference

python scripts/main.py -a "abstract.txt" -s scientific -o layout.md

Example 3: JSON Output for Integration

python scripts/main.py -a "$(cat abstract.txt)" -f json > result.json

Output Format

The Skill produces a structured analysis including:

1. Key Concepts Extracted

  • Core research topic
  • Methods/techniques used
  • Key findings/results
  • Implications

2. Visual Element Recommendations

  • Recommended icons/symbols
  • Color palette suggestions
  • Layout structure

3. AI Art Prompts

  • Midjourney Prompt: Optimized for Midjourney v6
  • DALL-E Prompt: Optimized for DALL-E 3

4. Layout Blueprint

  • Grid-based layout suggestion
  • Element positioning
  • Flow direction

Example Output

# Graphical Abstract Recommendation

## Abstract Summary
**Topic**: Deep learning protein structure prediction
**Method**: Transformer + Geometric constraints
**Result**: State-of-the-art CASP14 accuracy

## Key Concepts
- ๐Ÿงฌ Protein structures
- ๐Ÿค– Neural networks
- ๐Ÿ“Š Accuracy metrics

## Visual Elements
| Element | Symbol | Position | Color |
|---------|--------|----------|-------|
| Core Concept | Brain + DNA | Center | Blue |
| Method | Neural Network | Left | Purple |
| Result | Trophy/Chart | Right | Gold |

## Layout Suggestion

โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”‚ [Title/Concept] โ”‚ โ”‚ ๐Ÿงฌ๐Ÿค– โ”‚ โ”œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ค โ”‚ Input โ”‚ Process โ”‚ Output โ”‚ โ”‚ ๐Ÿ“ฅ โ”‚ โš™๏ธ โ”‚ ๐Ÿ“ˆ โ”‚ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ดโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ดโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜


## AI Art Prompts

Metadata

Author@aipoch-ai
Stars4473
Views0
Updated2026-05-01
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Add to Configuration

Paste this into your clawhub.json to enable this plugin.

{
  "plugins": {
    "official-aipoch-ai-graphical-abstract-wizard": {
      "enabled": true,
      "auto_update": true
    }
  }
}

Tags

#academic#ai-art#research
Safety NoteClawKit audits metadata but not runtime behavior. Use with caution.

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