infographics – Data & Science skill for AI agents

Infographics

Overview

Infographics are visual representations of information, data, or knowledge designed to present complex content quickly and clearly. This skill uses Nano Banana 2 AI for infographic generation with Gemini 3.7 Flash quality review and Perplexity Sonar for research.

How it works:

• (Optional) Research phase: Gather candidate facts and source records using Perplexity Sonar Pro
• Describe your infographic in natural language
• Nano Banana 2 generates raster drafts from your content
• Gemini 3.7 Flash reviews quality against document-type thresholds
• Smart iteration: Regenerates when review requests improvements, within the iteration budget
• Inspect every final image at its intended display size and check claims against sources

Quality Thresholds by Document Type:

| Document Type | Threshold | Description |

|---------------|-----------|-------------|

| marketing | 8.5/10 | Marketing materials - must be compelling |

| report | 8.0/10 | Business reports - professional quality |

| presentation | 7.5/10 | Slides, talks - clear and engaging |

| social | 7.0/10 | Social media content |

| internal | 7.0/10 | Internal use |

| draft | 6.5/10 | Working drafts |

| default | 7.5/10 | General purpose |

Simply describe what you want, and Nano Banana 2 creates it.

Quick Start

Install the only runtime dependency in your chosen Python environment (python -m pip install requests),

then set OPENROUTER_API_KEY. Examples below illustrate CLI usage; paid generation was not

executed during this review. Scripts accept PNG output paths only.

Generate a draft by describing it:

# Generate a list infographic (default threshold 7.5/10)
python skills/infographics/scripts/generate_infographic.py \
  "5 benefits of regular exercise" \
  -o figures/exercise_benefits.png --type list

# Generate for marketing (highest threshold: 8.5/10)
python skills/infographics/scripts/generate_infographic.py \
  "Product features comparison" \
  -o figures/product_comparison.png --type comparison --doc-type marketing

# Generate with corporate style
python skills/infographics/scripts/generate_infographic.py \
  "Company milestones 2010-2025" \
  -o figures/timeline.png --type timeline --style corporate

# Generate with colorblind-safe palette
python skills/infographics/scripts/generate_infographic.py \
  "Heart disease statistics worldwide" \
  -o figures/health_stats.png --type statistical --palette wong

# Generate WITH RESEARCH for accurate, up-to-date data
python skills/infographics/scripts/generate_infographic.py \
  "Global AI market size and growth projections" \
  -o figures/ai_market.png --type statistical --research

What happens behind the scenes:

1. (Optional) Research: Perplexity Sonar Pro gathers candidate facts with source annotations

2. Generation 1: Nano Banana 2 creates initial infographic following design best practices

3. Review 1: Gemini 3.7 Flash evaluates quality against document-type threshold

4. Decision: Stop when the scored review meets threshold and requests no further changes

5. If improvements are requested: Retain content and source context, refine the prompt, regenerate

6. Repeat: Until quality meets threshold or the iteration budget is reached; stop on API failure and keep the latest saved draft

Smart Iteration Benefits:

• ✅ Saves API calls if first generation is good enough
• ✅ Higher quality standards for marketing materials
• ✅ Faster turnaround for drafts/internal use
• ✅ Appropriate quality for each use case

Output: Versioned PNGs plus a review log with models, scores, quality_met, and termination_reason. A saved image (success: true) can still be unreviewed or below threshold. Human factual and visual checks remain required.

When to Use This Skill

Use the infographics skill when:

• Presenting data or statistics in a visual format
• Creating timeline visualizations for project milestones or history
• Explaining processes, workflows, or step-by-step guides
• Comparing options, products, or concepts side-by-side
• Summarizing key points in an engaging visual format
• Creating geographic or map-based data visualizations
• Building hierarchical or organizational charts
• Designing social media content or marketing materials

Use scientific-schematics instead for:

• Technical flowcharts and circuit diagrams
• Biological pathways and molecular diagrams
• Neural network architecture diagrams
• CONSORT/PRISMA methodology diagrams

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Research Integration

Automatic Data Gathering (--research)

When creating infographics that require accurate, up-to-date data, use the --research flag to gather candidate facts and statistics using Perplexity Sonar Pro. The script preserves source annotations; it does not independently verify claims or source relevance. For scientific or medical publication, verify primary sources before including the resulting numbers.

# Research and generate statistical infographic
python skills/infographics/scripts/generate_infographic.py \
  "Global renewable energy adoption rates by country" \
  -o figures/renewable_energy.png --type statistical --research

# Research for timeline infographic
python skills/infographics/scripts/generate_infographic.py \
  "History of artificial intelligence breakthroughs" \
  -o figures/ai_history.png --type timeline --research

# Research for comparison infographic
python skills/infographics/scripts/generate_infographic.py \
  "Electric vehicles vs hydrogen vehicles comparison" \
  -o figures/ev_hydrogen.png --type comparison --research

What Research Provides

The research phase automatically:

1. Gathers Key Facts: 5-8 relevant facts and statistics about the topic

2. Provides Context: Background information for accurate representation

3. Requests Data Points: Numbers with units, populations, denominators, and dates

4. Preserves Sources: OpenRouter URL-citation annotations, plus optional provider citation fields

5. Dates the Request: Uses the current date while preserving historical event dates

When to Use Research

Enable research (--research) for:

• Statistical infographics requiring accurate numbers
• Market data, industry statistics, or trends
• Scientific or medical information
• Current events or recent developments
• Any topic where accuracy is critical

Skip research for:

• Simple conceptual infographics
• Internal process documentation
• Topics where you provide all the data in the prompt
• Speed-critical generation

Research Output

When research is enabled, additional files are created:

• {name}_research.json - Research answer and returned source records (when research succeeds)
• Research content and source records remain in generation, review, and refinement prompts
• Failed research is recorded in the review log; generation continues with the supplied prompt

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Infographic Types

Ten types are supported via --type: statistical, timeline, process, comparison,

list, geographic, hierarchical, anatomical, resume, and social. What each is

for, the data shape it expects, and worked prompts are in

[references/infographic_type_catalog.md](references/infographic_type_catalog.md) and

[references/infographic_types.md](references/infographic_types.md).

Style Presets

Industry Styles (--style)

| Style | Colors | Best For |

|-------|--------|----------|

| corporate | Navy, steel blue, gold | Business reports, finance |

| healthcare | Medical blue, cyan, light cyan | Medical, wellness |

| technology | Tech blue, slate, violet | Software, data, AI |

| nature | Forest green, mint, earth brown | Environmental, organic |

| education | Academic blue, light blue, coral | Learning, academic |

| marketing | Coral, teal, yellow | Social media, campaigns |

| finance | Navy, gold, green/red | Investment, banking |

| nonprofit | Warm orange, sage, sand | Social causes, charities |

# Corporate style
python skills/infographics/scripts/generate_infographic.py \
  "Q4 Results" -o q4.png --type statistical --style corporate

# Healthcare style
python skills/infographics/scripts/generate_infographic.py \
  "Patient Journey" -o journey.png --type process --style healthcare

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Colorblind-Safe Palettes

Available Palettes (--palette)

| Palette | Colors | Description |

|---------|--------|-------------|

| wong | Seven chromatic colors plus black | Okabe-Ito palette popularized by Wong |

| ibm | Ultramarine, indigo, magenta, orange, gold | Legacy five-color preset |

| tol | Nine-color muted palette | Categorical data; pale gray reserved for missing data |

# Wong's colorblind-safe palette
python skills/infographics/scripts/generate_infographic.py \
  "Survey results by category" -o survey.png --type statistical --palette wong

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Smart Iterative Refinement and CLI

The generate-review-refine loop, every c

… (full content is in the download package)