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infographics

Design & creation

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Updated 10-21 16:21

About this skill

Infographics

Overview

Infographics are visual representations of information, data, or knowledge designed to present complex content quickly and clearly. This skill uses Nano Banana Pro AI for infographic generation with Gemini 3.6 Flash quality review and Perplexity Sonar for research.

How it works:

  • (Optional) Research phase: Gather accurate facts and statistics using Perplexity Sonar
  • Describe your infographic in natural language
  • Nano Banana Pro generates publication-quality infographics automatically
  • Gemini 3.6 Flash reviews quality against document-type thresholds
  • Smart iteration: Only regenerates if quality is below threshold
  • Professional-ready output in minutes
  • No design skills required

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 Pro creates it.

Quick Start

Generate any infographic by simply 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 gathers accurate facts, statistics, and data
  2. Generation 1: Nano Banana Pro creates initial infographic following design best practices
  3. Review 1: Gemini 3.6 Flash evaluates quality against document-type threshold
  4. Decision: If quality >= threshold → DONE (no more iterations needed!)
  5. If below threshold: Improved prompt based on critique, regenerate
  6. 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 marketing materials
  • ✅ Faster turnaround for drafts/internal use
  • ✅ Appropriate quality for each use case

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

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

Research Integration

Automatic Data Gathering (--research)

When creating infographics that require accurate, up-to-date data, use the --research flag to automatically gather facts and statistics using Perplexity Sonar Pro.

# 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. Finds Data Points: Specific numbers, percentages, and dates
  4. Cites Sources: Mentions major studies or sources
  5. Prioritizes Recency: Focuses on 2023-2026 information

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 - Raw research data and sources
  • Research content is automatically incorporated into the infographic prompt

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 and 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

Colorblind-Safe Palettes

Available Palettes (--palette)

Palette Colors Description
wong Orange, sky blue, green, blue, vermillion Most widely recommended
ibm Ultramarine, indigo, magenta, orange, gold IBM's accessible palette
tol 12-color extended palette For many categories 
# Wong's colorblind-safe palette
python skills/infographics/scripts/generate_infographic.py \
  "Survey results by category" -o survey.png --type statistical --palette wong

Smart Iterative Refinement and CLI

The generate-review-refine loop, every command-line option, and configuration are in references/iterative_refinement.md.

Prompt Engineering Tips

Be Specific About Content

✓ Good prompts (specific, detailed):

"5 benefits of meditation: reduces stress, improves focus, 
better sleep, lower blood pressure, emotional balance"

✗ Avoid vague prompts:

"meditation infographic"

Include Data Points

✓ Good:

"Market growth from $10B (2020) to $45B (2025), CAGR 35%"

✗ Vague:

"market is growing"

Specify Visual Elements

✓ Good:

"Timeline showing 5 milestones with icons for each event"

Reference Files

For detailed guidance, load these reference files:

  • references/infographic_types.md: Extended templates for all 10+ types
  • references/design_principles.md: Visual hierarchy, layout, typography
  • references/color_palettes.md: Full palette specifications

Troubleshooting

Common Issues

Problem: Text in infographic is unreadable

  • Solution: Reduce text content; use --type to specify layout type

Problem: Colors clash or are inaccessible

  • Solution: Use --palette wong for colorblind-safe colors

Problem: Quality score too low

  • Solution: Increase iterations with --iterations 3; use more specific prompt

Problem: Wrong infographic type generated

  • Solution: Always specify --type flag for consistent results

Integration with Other Skills

This skill works synergistically with:

  • scientific-schematics: For technical diagrams and flowcharts
  • market-research-reports: Infographics for business reports
  • scientific-slides: Infographic elements for presentations
  • generate-image: For non-infographic visual content

Quick Reference Checklist

Before generating:

  • Clear, specific content description
  • Infographic type selected (--type)
  • Style appropriate for audience (--style)
  • Output path specified (-o)
  • API key configured

After generating:

  • Review the generated image
  • Check the review log for scores
  • Regenerate with more specific prompt if needed

Use this skill to create professional, accessible, and visually compelling infographics using the power of Nano Banana Pro AI with intelligent quality review.

Agent operating procedure

  1. Check the environment. Confirm the data source, the message each figure must convey, and the target medium (journal, poster, slides).
  2. Pin down the inputs. Confirm formats, identifiers and parameters from the data or the user. Ask rather than guess any value that changes the result.
  3. Run a small version first. Render one figure at final size and check legibility before producing the full set.
  4. Execute the full task using the instructions and references above.
  5. Validate the result. Axes, units and error bars are labeled and defined; colours are colour-blind safe; numbers match the underlying data.
  6. Report. State what was run (versions, commands, parameters), what was checked, and what is still uncertain.
If this happens Do this
Text is unreadable at final size Increase font sizes or simplify the panel rather than shrinking it.
A function, flag or endpoint in these instructions is missing in the installed version Check the installed version's own documentation (help(), --help, official docs), adapt, and tell the user. Never invent an API.
A required input, identifier or parameter is ambiguous Ask the user, or state the assumption explicitly before running.

Integrity rules

  • Never fabricate results, parameters, identifiers, citations or statistics. If something cannot be run or verified, say so plainly.
  • Never alter data to improve a figure's appearance; apply image adjustments uniformly and disclose them.
  • Treat version-specific details here as possibly outdated: confirm them against the official documentation for the installed version.
  • Ask before actions that cost money, consume shared GPUs or cloud quota, touch personal or patient data, or cannot be undone.

Related skills

  • scientific-schematics: Generates publication-style scientific diagrams as raster PNG images from a natural-language prompt, using Nano Banana 2 via OpenRouter, th…
  • generate-image: Generate or edit images with AI models through the OpenRouter Image API (Gemini, Seedream, Recraft, GPT-Image, Riverflow).
  • academic-plotting: Generates publication-quality figures for ML papers from research context.