Scientific Schematics

Scientific Schematics and Diagrams

Overview

Generate publication-quality scientific diagrams using AI with smart iterative refinement.

How it works:

• Describe your diagram in natural language
• AI generates publication-quality images
• AI reviews quality against document-type thresholds
• Smart iteration: Only regenerates if quality is below threshold
• Publication-ready output in minutes
• No coding, templates, or manual drawing required

Quality Thresholds by Document Type:

Quick Start

Create any scientific diagram by simply describing it:

# Generate for journal paper (highest quality threshold: 8.5/10)
python scripts/generate_schematic.py "CONSORT participant flow diagram with 500 screened, 150 excluded, 350 randomized" -o figures/consort.png --doc-type journal

# Generate for presentation (lower threshold: 6.5/10 - faster)
python scripts/generate_schematic.py "Transformer encoder-decoder architecture showing multi-head attention" -o figures/transformer.png --doc-type presentation

# Generate for poster (moderate threshold: 7.0/10)
python scripts/generate_schematic.py "MAPK signaling pathway from EGFR to gene transcription" -o figures/mapk_pathway.png --doc-type poster

# Custom max iterations (max 2)
python scripts/generate_schematic.py "Complex circuit diagram with op-amp, resistors, and capacitors" -o figures/circuit.png --iterations 2 --doc-type journal

What happens behind the scenes:

1. Generation 1: AI creates initial image following scientific diagram best practices
2. Review 1: AI evaluates quality against document-type threshold
3. Decision: If quality >= threshold → DONE (no more iterations needed!)
4. If below threshold: Improved prompt based on critique, regenerate
5. Repeat: Until quality meets threshold OR max iterations reached

Smart Iteration Benefits:

• ✅ Saves API calls if first generation is good enough
• ✅ Higher quality standards for journal papers
• ✅ Faster turnaround for presentations/posters
• ✅ Appropriate quality for each use case

Output: Versioned images plus a detailed review log with quality scores, critiques, and early-stop information.

Command-Line Options

# Basic usage (default threshold 7.5/10)
python scripts/generate_schematic.py "diagram description" -o output.png

# Specify document type for appropriate quality threshold
python scripts/generate_schematic.py "diagram" -o out.png --doc-type journal      # 8.5/10
python scripts/generate_schematic.py "diagram" -o out.png --doc-type conference   # 8.0/10
python scripts/generate_schematic.py "diagram" -o out.png --doc-type poster       # 7.0/10
python scripts/generate_schematic.py "diagram" -o out.png --doc-type presentation # 6.5/10

# Custom max iterations (1-2)
python scripts/generate_schematic.py "complex diagram" -o diagram.png --iterations 2

# Verbose output (see all API calls and reviews)
python scripts/generate_schematic.py "flowchart" -o flow.png -v

# Provide API key via flag
python scripts/generate_schematic.py "diagram" -o out.png --api-key "sk-or-v1-..."

# Combine options
python scripts/generate_schematic.py "neural network" -o nn.png --doc-type journal --iterations 2 -v

AI Generation Best Practices

Effective Prompts for Scientific Diagrams:

✓ Good prompts (specific, detailed):

• "CONSORT flowchart showing participant flow from screening (n=500) through randomization to final analysis"
• "Transformer neural network architecture with encoder stack on left, decoder stack on right, showing multi-head attention and cross-attention connections"
• "Biological signaling cascade: EGFR receptor → RAS → RAF → MEK → ERK → nucleus, with phosphorylation steps labeled"
• "Block diagram of IoT system: sensors → microcontroller → WiFi module → cloud server → mobile app"

✗ Avoid vague prompts:

• "Make a flowchart" (too generic)
• "Neural network" (which type? what components?)
• "Pathway diagram" (which pathway? what molecules?)

Key elements to include:

• Type: Flowchart, architecture diagram, pathway, circuit, etc.
• Components: Specific elements to include
• Flow/Direction: How elements connect (left-to-right, top-to-bottom)
• Labels: Key annotations or text to include
• Style: Any specific visual requirements

Scientific Quality Guidelines (automatically applied):

• Clean white/light background
• High contrast for readability
• Clear, readable labels (minimum 10pt)
• Professional typography (sans-serif fonts)
• Colorblind-friendly colors (Okabe-Ito palette)
• Proper spacing to prevent crowding
• Scale bars, legends, axes where appropriate

Examples

Example 1: CONSORT Flowchart

python scripts/generate_schematic.py \
  "CONSORT participant flow diagram for randomized controlled trial. \
  Start with 'Assessed for eligibility (n=500)' at top. \
  Show 'Excluded (n=150)' with reasons: age<18 (n=80), declined (n=50), other (n=20). \
  Then 'Randomized (n=350)' splits into two arms: \
  'Treatment group (n=175)' and 'Control group (n=175)'. \
  Each arm shows 'Lost to follow-up' (n=15 and n=10). \
  End with 'Analyzed' (n=160 and n=165). \
  Use blue boxes for process steps, orange for exclusion, green for final analysis." \
  -o figures/consort.png

Example 2: Neural Network Architecture

python scripts/generate_schematic.py \
  "Transformer encoder-decoder architecture diagram. \
  Left side: Encoder stack with input embedding, positional encoding, \
  multi-head self-attention, add & norm, feed-forward. \
  Right side: Decoder stack with output embedding, positional encoding, \
  masked self-attention, add & norm, cross-attention (receiving from encoder), \
  add & norm, feed-forward, add & norm, linear & softmax. \
  Show cross-attention connection from encoder to decoder with dashed line. \
  Use light blue for encoder, light red for decoder. \
  Label all components clearly." \
  -o figures/transformer.png --iterations 2

Example 3: Biological Pathway

python scripts/generate_schematic.py \
  "MAPK signaling pathway diagram. \
  Start with EGFR receptor at cell membrane (top). \
  Arrow down to RAS (with GTP label). \
  Arrow to RAF kinase. \
  Arrow to MEK kinase. \
  Arrow to ERK kinase. \
  Final arrow to nucleus showing gene transcription. \
  Label each arrow with 'phosphorylation' or 'activation'. \
  Use rounded rectangles for proteins, different colors for each. \
  Include membrane boundary line at top." \
  -o figures/mapk_pathway.png

Example 4: System Architecture

python scripts/generate_schematic.py \
  "IoT system architecture block diagram. \
  Bottom layer: Sensors (temperature, humidity, motion) in green boxes. \
  Middle layer: Microcontroller (ESP32) in blue box. \
  Connections to WiFi module (orange box) and Display (purple box). \
  Top layer: Cloud server (gray box) connected to mobile app (light blue box). \
  Show data flow arrows between all components. \
  Label connections with protocols: I2C, UART, WiFi, HTTPS." \
  -o figures/iot_architecture.png

When to Use This Skill

This skill should be used when:

• Creating neural network architecture diagrams (Transformers, CNNs, RNNs, etc.)
• Illustrating system architectures and data flow diagrams
• Drawing methodology flowcharts for study design (CONSORT, PRISMA)
• Visualizing algorithm workflows and processing pipelines
• Creating circuit diagrams and electrical schematics
• Depicting biological pathways and molecular interactions
• Generating network topologies and hierarchical structures
• Illustrating conceptual frameworks and theoretical models
• Designing block diagrams for technical papers

Integration with Other Skills

This skill works synergistically with:

• Scientific Writing - Diagrams follow figure best practices
• Scientific Visualization - Shares color palettes and styling
• LaTeX Posters - Generate diagrams for poster presentations
• Research Grants - Methodology diagrams for proposals
• Peer Review - Evaluate diagram clarity and accessibility

Quick Reference Checklist

Before submitting diagrams, verify:

Visual Quality

• High-quality image format (PNG from AI generation)
• No overlapping elements (AI handles automatically)
• Adequate spacing between all components (AI optimizes)
• Clean, professional alignment
• All arrows connect properly to intended targets

Accessibility

• Colorblind-safe palette (Okabe-Ito) used
• Works in grayscale (tested with accessibility checker)
• Sufficient contrast between elements (verified)
• Redundant encoding where appropriate (shapes + colors)
• Colorblind simulation passes all checks

Typography and Readability

• Text minimum 7-8 pt at final size
• All elements labeled clearly and completely
• Consistent font family and sizing
• No text overlaps or cutoffs
• Units included where applicable

Publication Standards

• Consistent styling with other figures in manuscript
• Comprehensive caption written with all abbreviations defined
• Referenced appropriately in manuscript text
• Meets journal-specific dimension requirements
• Exported in required format for journal (PDF/EPS/TIFF)

Quality Verification (Required)

• Ran quality checks and achieved PASS status
• Reviewed overlap detection report (zero high-severity overlaps)
• Passed accessibility verification (grayscale and colorblind)
• Resolution validated at target DPI (300+ for print)
• Visual quality report generated and reviewed
• All quality reports saved with figure files

Documentation and Version Control

• Source files (.py) saved for future revision
• Quality reports archived in directory
• Configuration parameters documented (colors, spacing, sizes)
• Git commit includes source, output, and quality reports
• README or comments explain how to regenerate figure

Final Integration Check

• Figure displays correctly in compiled manuscript
• Cross-references work (\ref{} points to correct figure)
• Figure number matches text citations
• Caption appears on correct page relative to figure
• No compilation warnings or errors related to figure

Getting Started

Simplest possible usage:

python scripts/generate_schematic.py "your diagram description" -o output.png

Use this skill to create clear, accessible, publication-quality diagrams that effectively communicate complex scientific concepts. The AI-powered workflow with iterative refinement ensures diagrams meet professional standards.

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