Infographic Generator logo

Infographic Generator

Organization
Affitor
infographic-generator

Generate branded infographic specifications from any content or data. Outputs structured layout, copy, data visualization, and color scheme — ready to render as HTML/CSS, Satori, Canva, or any design tool. Use this skill when the user wants an infographic, data visual, social media image, comparison chart, stat card, or says "create an infographic for [content]", "make a visual for my LinkedIn post", "design an image for [topic]", "stat graphic for [data]", "comparison infographic", "branded image", "social media graphic", "infographic for [blog post]", "data visualization", "visual content", "image for my post", "LinkedIn carousel image", "feature comparison chart", "pricing table image".

Overview

PublisherAffitor
Repositoryaffiliate-skills
Skill nameinfographic-generator
Stars
705
Forks
209
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Affitor on GitHub. Read the source before you install it.

Installation

Install the Infographic Generator AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Affitor/affiliate-skills/tree/main/skills/content/infographic-generator
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Affitor/affiliate-skills.git /tmp/affiliate-skills
mkdir -p .claude/skills
cp -r /tmp/affiliate-skills/skills/content/infographic-generator .claude/skills/infographic-generator
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Infographic Generator in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Infographic Generator on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Infographic Generator is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Infographic Generator

Generate complete infographic specifications from any content, data, or topic. Outputs structured layout + all copy + data points + color scheme — ready to render as HTML/CSS, with Satori (server-side), in Canva, Figma, or any design tool.

LinkedIn posts with images get 2-3x more engagement. This skill turns your content into visual assets without design skills.

Inspired by content-pipeline's Satori rendering: AI writes the content → structured spec → rendered as a branded image.

Stage

This skill belongs to Stage S2: Content

When to Use

  • After viral-post-writer creates a LinkedIn post — add a visual
  • After content-research-brief collects stats — visualize them
  • When creating comparison content — feature/pricing comparison chart
  • When sharing data or stats — stat highlight cards
  • When creating a listicle — visual checklist or numbered list
  • For any social media post that would benefit from a branded image

Input Schema

yaml
content: string                # (required) Content to visualize — post text, data, or article
infographic_type: string       # (optional, default: auto-detected)
                               # "stat_highlight" — 1-3 key numbers, large and bold
                               # "comparison" — side-by-side product/feature comparison
                               # "process_flow" — step-by-step workflow or how-to
                               # "checklist" — list of items with checkmarks
                               # "timeline" — chronological events
                               # "data_chart" — bar/pie chart representation
                               # "quote_card" — featured quote with attribution
                               # "feature_grid" — grid of features/benefits with icons
platform: string               # (optional, default: "linkedin")
                               # "linkedin" — 1080×1350 (portrait, optimal engagement)
                               # "instagram" — 1080×1080 (square)
                               # "twitter" — 1200×675 (landscape)
                               # "facebook" — 1200×630
                               # "blog" — 1200×800 (featured image)
brand: object                  # (optional) Brand customization
  name: string                 # Company/personal brand name
  primary_color: string        # Hex — "#0066FF"
  secondary_color: string      # Hex — "#1A1A2E"
  accent_color: string         # Hex — "#FF6B35"
  font_style: string           # "modern" | "classic" | "bold" | "minimal"
  logo_text: string            # Text-based logo — "Affitor" | "@yourhandle"
output_format: string          # (optional, default: "spec")
                               # "spec" — structured JSON spec (for any renderer)
                               # "html" — renderable HTML/CSS (self-contained)
                               # "both" — spec + HTML

Workflow

Step 1: Analyze Content and Select Type

Read the input content and detect the best infographic type:

Content PatternAuto-detected Type
Contains 1-3 prominent numbers/statsstat_highlight
Contains "vs", comparison datacomparison
Contains numbered steps or a processprocess_flow
Contains a list of items (3-10)checklist or feature_grid
Contains dates or chronological eventstimeline
Contains a notable quotequote_card
Contains percentages or proportionsdata_chart

If infographic_type is provided, use that. Otherwise auto-detect.

Step 2: Extract Visual Data

From the content, extract exactly what needs to appear in the infographic:

For stat_highlight:

yaml
stats:
  - number: "30%"        # The big number
    label: "commission"   # What it measures
    context: "recurring"  # Additional context
  - number: "60"
    label: "cookie days"
    context: "industry avg: 30"

For comparison:

yaml
items:
  - name: "HeyGen"
    features:
      - label: "Commission"
        value: "30% recurring"
        highlight: true         # winner for this row
      - label: "Cookie"
        value: "60 days"
        highlight: true
  - name: "Synthesia"
    features:
      - label: "Commission"
        value: "25% one-time"
        highlight: false
      - label: "Cookie"
        value: "30 days"
        highlight: false

For process_flow:

yaml
steps:
  - number: 1
    title: "Research"
    description: "Find winning programs"
    icon: "🔍"
  - number: 2
    title: "Create"
    description: "Write content that converts"
    icon: "✍️"

For checklist:

yaml
items:
  - text: "Recurring commission"
    checked: true
  - text: "60+ day cookie"
    checked: true
  - text: "Free trial available"
    checked: true
  - text: "Dedicated affiliate manager"
    checked: false

Step 3: Design Layout

Based on type + platform, define the layout:

Platform dimensions:

PlatformWidthHeightAspect
LinkedIn108013504:5 (portrait)
Instagram108010801:1 (square)
Twitter120067516:9 (landscape)
Facebook1200630~2:1
Blog12008003:2

Layout structure (all types):

┌─────────────────────────────┐
│         HEADER              │  10-15% height
│    Headline / Title         │
├─────────────────────────────┤
│                             │
│         BODY                │  70-80% height
│    Data / Content           │
│    (type-specific layout)   │
│                             │
├─────────────────────────────┤
│         FOOTER              │  10% height
│    Brand / CTA / Source     │
└─────────────────────────────┘

Step 4: Generate Color Scheme

If brand colors provided: Use them directly.

If no brand colors: Generate a professional palette:

yaml
# Default professional palette options
palettes:
  dark_modern:       # Dark background, light text
    bg: "#1A1A2E"
    text: "#FFFFFF"
    accent: "#0066FF"
    secondary: "#16213E"
    
  light_clean:       # Light background, dark text
    bg: "#FFFFFF"
    text: "#1A1A2E"
    accent: "#0066FF"
    secondary: "#F0F4F8"
    
  warm_bold:         # Warm tones
    bg: "#FFF8F0"
    text: "#2D2D2D"
    accent: "#FF6B35"
    secondary: "#FFE8D6"
    
  dark_gradient:     # Gradient dark
    bg: "linear-gradient(135deg, #1A1A2E, #16213E)"
    text: "#FFFFFF"
    accent: "#00D4AA"
    secondary: "#2A2A4A"

Auto-select based on platform:

  • LinkedIn → dark_modern or light_clean (professional)
  • Twitter → dark_gradient or warm_bold (attention-grabbing)
  • Instagram → Any (most visual flexibility)

Step 5: Generate All Copy

Write every piece of text that appears in the infographic:

yaml
copy:
  headline: string          # Main title — bold, short (max 8 words)
  subheadline: string       # Optional supporting line
  body_items: string[]      # Data labels, descriptions, etc.
  cta: string               # Call-to-action text — "Link in bio" | "See comments for link"
  footer: string            # Brand name or @handle
  source: string            # "Data: openaffiliate.dev" or source attribution

Copy rules:

  • Headlines: 3-8 words, bold claim or specific number
  • All text must be readable at mobile scale (not too small)
  • No more than 50 total words on the infographic (less = better)
  • Data > adjectives (show numbers, not "amazing" or "incredible")

Step 6: Output

Spec output (default):

Complete structured spec that any renderer can consume:

yaml
infographic_spec:
  type: string
  platform: string
  dimensions:
    width: number
    height: number
  colors:
    background: string
    text: string
    accent: string
    secondary: string
  layout:
    header: object
    body: object
    footer: object
  data: object              # Type-specific data (stats, comparison items, steps, etc.)
  copy:
    headline: string
    subheadline: string
    body_items: string[]
    cta: string
    footer: string
    source: string

HTML output (if output_format is "html" or "both"):

Generate a self-contained HTML file with inline CSS that renders the infographic at exact dimensions. This can be:

  • Opened in a browser and screenshotted
  • Rendered server-side with Satori or Puppeteer
  • Used as a starting point for design iteration
html
<!-- Self-contained, no external dependencies -->
<div style="width: 1080px; height: 1350px; ...">
  <!-- Header -->
  <!-- Body (type-specific) -->
  <!-- Footer -->
</div>

Step 7: Self-Validation

Before presenting output, verify:

  • Total word count on infographic ≤ 50 words
  • All text readable at 50% zoom (minimum effective font size)
  • Color contrast meets accessibility (WCAG AA: 4.5:1 ratio)
  • Data points are accurate and attributed
  • Layout doesn't feel cramped — whitespace is intentional
  • Platform dimensions are correct

If any check fails, fix before delivering.

Output Format

markdown
## Infographic: [Headline]

### Spec
- **Type:** [stat_highlight]
- **Platform:** [LinkedIn] — 1080×1350
- **Colors:** [dark_modern] — bg: #1A1A2E, accent: #0066FF

### Preview (text representation)

┌─────────────────────────────────┐
│                                 │
│     HeyGen vs Synthesia         │
│     The Real Comparison         │
│                                 │
│  ┌──────────┐  ┌──────────┐    │
│  │  HeyGen  │  │Synthesia │    │
│  │          │  │          │    │
│  │ 30% rec. │  │ 25% once │    │
│  │ 60 days  │  │ 30 days  │    │
│  │ ★ 127    │  │ ★ 84     │    │
│  └──────────┘  └──────────┘    │
│                                 │
│     🏆 Winner: HeyGen           │
│                                 │
│  ───────────────────────────    │
│  @yourhandle · openaffiliate.dev │
└─────────────────────────────────┘

### Data

[Structured spec as YAML or JSON]

### HTML (if requested)

[Self-contained HTML/CSS code block]

### Next Steps
- Post to [platform] with your viral post from `viral-post-writer`
- Create variations for other platforms: `--platform instagram`
- Generate more infographics from different data in your `content-research-brief`

Error Handling

  • Content has no extractable data: Generate a quote_card or checklist type instead. Note: "No numerical data found. Created a [type] infographic instead."
  • Too much data for one infographic: Select top 3-5 most impactful data points. Note: "Content has [X] data points. Selected the [Y] most impactful for visual clarity. Consider creating multiple infographics."
  • No brand colors: Use default palette. Note: "No brand colors specified. Using [palette name]. Add brand colors for consistent branding."
  • HTML output too complex: Simplify layout. Infographics should be simple — complexity kills visual impact.

Examples

Example 1: User: "Make an infographic comparing HeyGen vs Synthesia for LinkedIn" → type: comparison, platform: linkedin (1080×1350) → Extract: commission, cookie, rating, price for each → Output: side-by-side comparison card with winner highlighted → Dark modern palette, bold numbers

Example 2: User: "Create a stat card from my research brief showing HeyGen's key numbers" → type: stat_highlight, platform: linkedin → Extract: "$60M raised", "40K businesses", "30% commission" → Output: 3 large numbers with labels and context

Example 3: User: "Visualize the affiliate funnel steps as an infographic" → type: process_flow, platform: blog (1200×800) → Steps: Research → Content → Landing → Deploy → Track → Optimize → Output: horizontal flow with icons and brief descriptions

Feedback & Issue Reporting

When this skill produces unexpected, incomplete, or incorrect output, generate a skill_feedback block (see shared/references/feedback-protocol.md for full schema).

Skill-specific failure modes:

  • No extractable data from content: Content is purely narrative, no stats/numbers. Report as data_quality.
  • HTML output doesn't render correctly: CSS issues, wrong dimensions, text overflow. Report as wrong_output with the HTML.
  • Too many words on infographic: >50 words makes it unreadable. Report as wrong_output.

Auto-detect triggers:

  • infographic_spec.data has <2 data points
  • Total word count in all copy fields > 60
  • Dimensions don't match declared platform

Report issues: GitHub Issues | Discussions

References

  • shared/references/social-data-providers.md — data sources for infographic content
  • shared/references/platform-rules.md — platform-specific image requirements
  • shared/references/flywheel-connections.md — master flywheel connection map
  • shared/references/feedback-protocol.md — issue detection and reporting standard

Flywheel Connections

Feeds Into

  • social-media-scheduler (S5) — infographic ready to schedule with post
  • landing-page-creator (S4) — infographic as hero image or section visual
  • email-drip-sequence (S5) — infographic as email visual content
  • bio-link-deployer (S5) — infographic in link hub

Fed By

  • content-research-brief (S2) — key stats and data for visualization
  • viral-post-writer (S2) — post content to create accompanying visual
  • affiliate-blog-builder (S3) — blog data for featured image infographic
  • trending-content-scout (S1) — engagement data for benchmark visuals
  • traffic-analyzer (S1) — traffic data for comparison infographics
  • comparison-post-writer (S3) — comparison data for visual format
  • commission-calculator (S1) — commission data for stat highlights

Feedback Loop

  • S6 posts with infographics vs without → performance-report shows engagement lift → prioritize infographic creation for high-value content

Quality Gate

Before delivering output, verify:

  1. Would I stop scrolling for this image?
  2. Can I understand the main point in under 3 seconds?
  3. Is the data accurate and attributed?
  4. Does it look professional, not like clip art?
  5. Is it readable on a phone screen?

Any NO → redesign before delivering.

yaml
chain_metadata:
  skill_slug: "infographic-generator"
  stage: "content"
  timestamp: string
  suggested_next:
    - "social-media-scheduler"
    - "viral-post-writer"
    - "landing-page-creator"

Frequently asked questions

What does the Infographic Generator AI skill do?

Generate branded infographic specifications from any content or data. Outputs structured layout, copy, data visualization, and color scheme — ready to render as HTML/CSS, Satori, Canva, or any design tool. Use this skill when the user wants an infographic, data visual, social media image, comparison chart, stat card, or says "create an infographic for [content]", "make a visual for my LinkedIn post", "design an image for [topic]", "stat graphic for [data]", "comparison infographic", "branded image", "social media graphic", "infographic for [blog post]", "data visualization", "visual content...

Why use Infographic Generator on TypingMind?

Because you install it once and use it with any model. Infographic Generator is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Infographic Generator in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Affitor/affiliate-skills/tree/main/skills/content/infographic-generator. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Infographic Generator?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Infographic Generator?

As many as you like. As long as a model supports skills, you can use Infographic Generator with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Infographic Generator AI skill free?

Yes. It is published on GitHub by Affitor under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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