Generate Visualizations Command

Automatically generate professional visualizations including Mermaid diagrams, data charts, token usage comparisons, and hero images for Medium articles and technical documentation.

How to Load MCP Resources

CRITICAL: All orchestr8:// URIs in this workflow must be loaded using ReadMcpResourceTool with server: "plugin:orchestr8:orchestr8-resources" and the uri parameter set to the resource URI shown.

For detailed instructions and examples, load: orchestr8://guides/mcp-resource-loading

Usage

# Generate all visualizations for a Medium article
/orchestr8:generate-visualizations medium/article.md

# Generate specific visualization types
/orchestr8:generate-visualizations medium/article.md --type=diagrams
/orchestr8:generate-visualizations medium/article.md --type=charts
/orchestr8:generate-visualizations medium/article.md --type=hero

# Generate from theme/topic
/orchestr8:generate-visualizations "AI optimization and token management"

# Generate for project documentation
/orchestr8:generate-visualizations . --type=diagrams

Phase 1: Analysis & Planning (0-20%)

→ Load Agent: orchestr8://agents/visualization-specialist

Activities:

Analyze article content or project codebase
Identify key concepts requiring visualization
Determine appropriate diagram types and data visualizations
Plan hero image concept if Medium article
Map technical architecture if code project

Outputs:

List of required visualizations with priorities
Themes and concepts for each visualization
File naming and organization plan

Success Criteria:

✅ All visualization opportunities identified
✅ Appropriate types selected for each concept
✅ Clear output directory structure planned

→ Checkpoint: Analysis complete, visualization plan ready

Phase 2: Mermaid Diagram Generation (20-45%)

→ Load: orchestr8://skills/mermaid-diagram-generation

Parallel Tracks:

Track 1: Architecture Diagrams

For technical content or code projects:

System Context (C4 L0): High-level system and external dependencies
Container Diagram (C4 L1): Applications, databases, services
Component Diagram (C4 L2): Internal components and relationships
Code Diagram (C4 L3): Class structures (if needed)

Track 2: Flow Diagrams

Data Flow: How information moves through the system
Sequence Diagrams: Temporal interactions and API calls
State Machines: Workflow states and transitions
User Journey: Decision trees and experience paths

Track 3: Data Diagrams

Entity Relationship: Database schema and relationships
Deployment Topology: Infrastructure and deployment architecture

Output Format:

<!-- Saved to: medium/diagrams/[type]-[description].md -->

# [Diagram Title]

**Purpose**: [What this diagram shows]

**Context**: [When to reference this diagram]

```mermaid
[Mermaid diagram code]

Key Points:

[Important aspect 1]
[Important aspect 2]


**Color Standards:**
- Blue (#1168bd): Internal systems/components
- Gray (#999999): External systems
- Green (#2d7a3e): Databases/persistence
- Red (#d9534f): Cache layers
- Orange (#f0ad4e): Message queues
- Light Blue (#5bc0de): User interfaces

**Success Criteria:**
- ✅ Diagrams render correctly in Mermaid
- ✅ Appropriate level of detail (not too complex)
- ✅ Clear labels and relationships
- ✅ Consistent color scheme
- ✅ Saved to organized directory structure

**→ Checkpoint:** Mermaid diagrams generated and validated

## Phase 3: Data Chart Generation (45-70%)

**→ Load:** orchestr8://skills/data-chart-generation

**Chart Types:**

### Performance Comparisons
- Token usage before/after
- Cost comparison charts
- Speed/latency improvements
- Memory usage reduction

### Metrics Visualization
- Time series data (usage over time)
- Distribution charts (load distribution)
- Comparison bars (method A vs method B)
- Pie charts (resource allocation)

**Technology Options:**

1. **Matplotlib + Python** (Best for complex charts)
   ```python
   python scripts/generate-chart.py \
     --type comparison \
     --data "Before: 200000, After: 5000" \
     --title "Token Usage Reduction" \
     --output medium/images/

Chart.js + Node (Web-ready, interactive)

node scripts/generate-chart.js \
  --type bar \
  --data data.json \
  --output medium/images/chart.png

Mermaid Charts (Simple, markdown-native)

%%{init: {'theme':'base'}}%%
pie title Token Distribution
    "Loaded Upfront" : 200000
    "Loaded On-Demand" : 5000

Output Requirements:

High resolution (1920px width minimum for hero images)
PNG format with transparency support
Optimized file size (<500KB for charts)
Clear labels, legend, and title
Professional color scheme

Success Criteria:

✅ Data accurately represented
✅ Charts are readable at small sizes
✅ Professional appearance
✅ Proper file naming and organization
✅ Alt text descriptions included

→ Checkpoint: Charts generated and verified

Phase 4: Screenshot Generation (70-85%)

→ Load: orchestr8://skills/screenshot-automation

Screenshot Types:

Code Examples

Syntax-highlighted code blocks
Terminal output captures
Configuration files

Application Screenshots

UI mockups or actual application views
Dashboard visualizations
Before/after comparisons

Diagram Renders

Mermaid diagrams rendered as images
Architecture visualizations
Flow diagrams

Technology Options:

Playwright for Web Screenshots

python scripts/screenshot.py \
  --url "https://mermaid.live/view?code=[encoded]" \
  --output medium/images/architecture.png

Carbon for Code Screenshots

python scripts/code-screenshot.py \
  --file src/example.ts \
  --theme monokai \
  --output medium/images/code-example.png

Mermaid CLI for Diagram Renders

mmdc -i diagram.mmd -o medium/images/diagram.png -w 1920 -b transparent

Success Criteria:

✅ High resolution (2x for retina)
✅ Proper cropping and margins
✅ Readable text at display size
✅ Professional appearance
✅ Consistent styling

→ Checkpoint: Screenshots captured and optimized

Phase 5: Hero Image Generation (85-95%)

→ Load: orchestr8://skills/medium-hero-image-generation

Activities:

Extract article theme and key concepts
Generate AI-powered hero image (DALL-E 3 or Stable Diffusion)
Create fallback gradient if APIs unavailable
Optimize image for Medium (1920x1080, <5MB)
Update article frontmatter with image path

Command:

python scripts/generate-hero-image.py \
  --file medium/article.md \
  --method dalle \
  --update

Success Criteria:

✅ Image matches article theme
✅ Professional, modern aesthetic
✅ Proper dimensions (1920x1080)
✅ Frontmatter updated
✅ Alt text included

→ Checkpoint: Hero image generated and integrated

Phase 6: Integration & Documentation (95-100%)

Activities:

1. Organize Output Files

medium/
├── article.md
├── images/
│   ├── hero.png
│   ├── token-comparison-chart.png
│   ├── architecture-diagram.png
│   └── code-screenshot.png
└── diagrams/
    ├── system-context.md
    ├── data-flow.md
    └── sequence-api-auth.md

2. Generate Index

Create medium/diagrams/README.md:

# Visualizations for [Article Title]

## Diagrams
- [System Context](system-context.md) - High-level architecture
- [Data Flow](data-flow.md) - Information movement
- [API Sequence](sequence-api-auth.md) - Authentication flow

## Charts
- ![Token Comparison](../images/token-comparison-chart.png)
- ![Cost Savings](../images/cost-comparison-chart.png)

## Hero Image
- ![Hero](../images/hero.png)

3. Update Article References

Add image references in article markdown:

![Architecture Overview](images/architecture-diagram.png)
*Figure 1: System architecture showing dynamic resource loading*

![Token Usage Comparison](images/token-comparison-chart.png)
*Figure 2: 97% reduction in token usage*

4. Generate Summary Report

Create medium/VISUALIZATIONS.md:

# Visualization Generation Report

**Article**: [Title]
**Generated**: [Date]

## Generated Visualizations

### Diagrams (Mermaid)
- ✅ System Context Diagram
- ✅ Data Flow Diagram
- ✅ Sequence Diagram (API Authentication)

### Charts
- ✅ Token Usage Comparison (97% reduction)
- ✅ Cost Comparison (40x savings)

### Screenshots
- ✅ Code Example: TypeScript implementation
- ✅ Architecture render

### Hero Image
- ✅ Generated with DALL-E 3
- ✅ Theme: AI optimization and dynamic loading
- ✅ Resolution: 1920x1080
- ✅ Frontmatter updated

## Usage in Article
All visualizations referenced in article with proper captions and alt text.

## Next Steps
- [ ] Review all visualizations for accuracy
- [ ] Verify rendering in Medium preview
- [ ] Optimize any oversized images
- [ ] Proceed with publishing workflow

Success Criteria:

✅ All files properly organized
✅ Index/README generated
✅ Article references updated
✅ Summary report created
✅ All visualizations validated

→ Checkpoint: Visualizations integrated and documented

Success Criteria

✅ Diagram Quality

Mermaid diagrams render correctly
Appropriate complexity level
Clear labels and relationships
Professional color scheme
Organized by category

✅ Chart Quality

Data accurately visualized
Professional appearance
Readable at thumbnail size
Proper legends and labels
Optimized file sizes

✅ Screenshot Quality

High resolution (retina-ready)
Professional cropping
Readable text
Consistent styling
Proper context

✅ Hero Image Quality

Matches article theme
Professional aesthetic
Correct dimensions (1920x1080)
Optimized file size (<5MB)
Alt text included

✅ Integration

All files properly organized
Article references updated
Documentation complete
Ready for publishing

Examples

For Medium Article

# Generate all visualizations for AI optimization article
/orchestr8:generate-visualizations medium/2025-11-11-ai-memory-optimization.md

# Output:
# - medium/images/hero.png (AI-generated hero image)
# - medium/images/token-comparison.png (Chart showing 97% reduction)
# - medium/images/architecture.png (System diagram)
# - medium/diagrams/system-context.md (C4 Level 0)
# - medium/diagrams/data-flow.md (Resource loading flow)

For Technical Documentation

# Generate architecture diagrams for project
/orchestr8:generate-visualizations . --type=diagrams

# Output:
# - .orchestr8/docs/diagrams/architecture-system-context.md
# - .orchestr8/docs/diagrams/architecture-containers.md
# - .orchestr8/docs/diagrams/dataflow-resource-loading.md
# - .orchestr8/docs/diagrams/sequence-fuzzy-matching.md

For Specific Concepts

# Generate visualizations for specific theme
/orchestr8:generate-visualizations "token usage optimization and caching"

# Output:
# - Token usage comparison charts
# - Caching strategy diagrams
# - Performance improvement visualizations

Configuration

Environment Variables

# AI Image Generation
export OPENAI_API_KEY="..."           # For DALL-E 3
export REPLICATE_API_TOKEN="..."      # For Stable Diffusion

# Screenshot Automation
export CARBON_API_KEY="..."           # For code screenshots (optional)

# Chart Generation
export CHART_THEME="professional"     # professional, minimal, vibrant
export CHART_DPI="300"                # Output DPI for charts

Output Directory Structure

# For Medium articles
medium/
├── images/           # All raster images (PNG, JPG)
└── diagrams/         # All Mermaid diagrams (.md files)

# For project documentation
.orchestr8/docs/
└── diagrams/        # All project diagrams

Tips for Best Results

Start with Analysis: Let the command analyze content thoroughly
Review Diagrams: Mermaid diagrams can be edited after generation
Iterate on Charts: Regenerate with different styles if needed
Check Dimensions: Verify all images meet platform requirements
Optimize Files: Run through optimization tools before publishing
Test Rendering: Preview diagrams in target platform (GitHub, Medium)
Use Consistent Style: Maintain visual consistency across all assets

Troubleshooting

Mermaid Diagrams Not Rendering

Validate syntax at https://mermaid.live
Check for special characters in labels
Ensure proper indentation
Verify diagram type is supported

Charts Look Unprofessional

Increase DPI setting (300-600 for print quality)
Use professional color palette
Add proper labels and legend
Ensure sufficient contrast

Hero Image Doesn't Match Theme

Refine theme description with specific keywords
Try different generation method (DALL-E vs Stable Diffusion)
Use gradient fallback and iterate
Manually select from Unsplash as alternative

Screenshots Have Poor Quality

Increase resolution (use 2x for retina)
Check viewport size settings
Verify proper cropping margins
Use higher quality compression

Related Resources:

/generate-visualizations

Generate Visualizations Command

How to Load MCP Resources

Usage

Phase 1: Analysis & Planning (0-20%)

Phase 2: Mermaid Diagram Generation (20-45%)

Track 1: Architecture Diagrams

Track 2: Flow Diagrams

Track 3: Data Diagrams

Phase 4: Screenshot Generation (70-85%)

Code Examples

Application Screenshots

Diagram Renders

Phase 5: Hero Image Generation (85-95%)

Phase 6: Integration & Documentation (95-100%)

1. Organize Output Files

2. Generate Index

3. Update Article References

4. Generate Summary Report

Success Criteria

Examples

For Medium Article

For Technical Documentation

For Specific Concepts

Configuration

Environment Variables

Output Directory Structure

Tips for Best Results

Troubleshooting

Mermaid Diagrams Not Rendering

Charts Look Unprofessional

Hero Image Doesn't Match Theme

Screenshots Have Poor Quality