Sumi - Artistic Infographic Generator

Generate beautiful infographics from any text topic using the Sumi pipeline. Claude analyzes, structures, and crafts prompts, then generates the image via Gemini API.

Sby Skills Guide Bot
ContentIntermediate
007/26/2026
Claude Code
#infographic#generative-art#data-visualization#sumi#creative-coding

Recommended for


name: sumi description: Generate artistic infographics from any topic. Runs the Sumi pipeline (analyze → structure → craft prompt → generate image) entirely within Claude Code. Use when "generate infographic", "create infographic", "sumi", "make an infographic about", or "visualize topic".

Sumi — Artistic Infographic Generator

Generate a beautiful infographic from a text topic. Claude does all the thinking (analysis, structuring, prompt crafting) using curated reference files. Only the final image generation calls an external API (Gemini).

Usage

The user provides:

  • topic (required): The subject or pasted text to turn into an infographic
  • style (optional): A style ID like ukiyo-e, bauhaus, sumi-e, etc.
  • layout (optional): A layout ID like bento-grid, hub-spoke, iceberg, etc.
  • aspect_ratio (optional): e.g. 16:9, 9:16, 1:1. Default: 16:9

If style or layout are not specified, recommend 3 combinations and let the user pick.

Reference Files

All reference files live in this skill's references/ directory:

  • references/analysis-framework.md — Framework for analyzing content
  • references/structured-content-template.md — Template for structuring content
  • references/base-prompt.md — Base prompt template for image generation
  • references/styles/{style-id}.md — Style definitions (60+ styles)
  • references/layouts/{layout-id}.md — Layout definitions (20 layouts)

IMPORTANT: Read the relevant reference files before each step. These contain the secret sauce — detailed visual instructions, color palettes, compositional patterns, and visual metaphor mappings that make the infographics excellent.

Instructions

Step 1: If style/layout not specified, recommend combinations

  1. Read references/analysis-framework.md
  2. Analyze the user's topic using the framework (just do the analysis yourself — you ARE Claude)
  3. Based on the content type, complexity, and audience, recommend 3 layout×style combinations:
    • best_match — most appropriate for the content
    • creative — unexpected, visually striking pairing
    • accessible — broadest appeal, balances clarity and aesthetics
  4. For each recommendation, give a 1-2 sentence rationale
  5. Ask the user to pick (1/2/3 or name their own)

To make good recommendations, consult the analysis framework's Content Type Classification table which maps content types to layouts and styles.

Step 2: Analyze content

Read references/analysis-framework.md and apply it to the topic. Produce a thorough analysis covering:

  • Content type classification (timeline, process, comparison, hierarchy, etc.)
  • Learning objectives (what the viewer will understand)
  • Audience analysis
  • Complexity assessment
  • Visual opportunity mapping
  • Data verbatim extraction (preserve all statistics, quotes, dates EXACTLY)

This analysis is internal working material — don't dump it on the user. Just mention you're analyzing.

Step 3: Structure content

Read references/structured-content-template.md and transform the analysis into designer-ready structured content:

  • Title and overview
  • Sections with key concepts, content points, visual elements, and text labels
  • All data points preserved verbatim
  • Clear visual element descriptions per section

Step 4: Craft the image generation prompt

This is where it all comes together. Read:

  • references/layouts/{selected-layout-id}.md — the full layout definition
  • references/styles/{selected-style-id}.md — the full style definition
  • references/base-prompt.md — the base prompt template

Then craft a rich, detailed image generation prompt with these sections:

Fixed header (one line):

Create a single {aspect_ratio} infographic in {Style Name} style using a {Layout Name} layout. All text in English. Use rich visual scenes with clear hierarchy and ample whitespace.

Layout Guidelines: Adapt the generic layout structure to this specific content. Replace placeholders with content-specific descriptions.

Style Guidelines: Include the FULL style description plus:

  • Color Palette with specific usage instructions
  • Visual Elements list
  • A Compositional Patterns table mapping content structures to style-specific compositions
  • Visual Metaphor Mappings that translate EACH content section into a concrete, style-specific visual scene
  • Typography instructions

Content: Describe each content section as a VISUAL SCENE. Each section must have:

  • A descriptive title (e.g., "CENTER HUB: The Castle")
  • A vivid description of what to DRAW — objects, characters, spatial layout, colors, mood
  • The exact text to render

Text Labels: Organize ALL text that should appear in the infographic, grouped by area: Title, Hub/Center, Section Labels, Section Content, Key Phrases, Attribution.

CRITICAL PROMPT CRAFTING RULES

  • Describe VISUAL SCENES, not abstract concepts. Tell the image generator what to DRAW.
  • Visual metaphor mappings must be SPECIFIC to the content AND style (e.g., for ukiyo-e: "Trust Signals → guardian komainu statues or a samurai standing watch")
  • Keep all source quotes and data VERBATIM — never summarize or rephrase
  • The prompt should be 1500-3000 words — rich enough for Gemini to produce a detailed infographic

Save the crafted prompt to a file for reference.

Step 5: Generate the image

The ONLY step that needs an external API call. Use the Sumi backend's image generator:

cd /Users/paolo/playground/sumi/backend && source .venv/bin/activate && python -c "
import asyncio
from sumi.engine.image_generator import generate_image

PROMPT = open('/tmp/sumi-prompt.md').read()
ASPECT_RATIO = 'ASPECT_RATIO_HERE'
OUTPUT_PATH = '/tmp/sumi-infographic.png'

async def main():
    path = await generate_image(prompt=PROMPT, output_path=OUTPUT_PATH, aspect_ratio=ASPECT_RATIO)
    print(f'Image saved: {path}')

asyncio.run(main())
"

Before running this:

  1. Write the crafted prompt to /tmp/sumi-prompt.md
  2. After generation, open the image with open <path> on macOS
  3. Tell the user the file path

Step 6: Iterate (if requested)

If the user wants to tweak:

  • Different style/layout: Re-do steps 4-5 with new references (skip analysis/structuring)
  • Prompt adjustments: Edit the saved prompt and re-run step 5
  • Content changes: Re-do from step 2

Available Styles

aged-academia, airline-travel-poster, art-nouveau, art-nouveau-mucha, atomic-age, axonometric, bauhaus, bold-graphic, botanical-illustration, chalkboard, charley-harper, claymation, constructivism, corporate-memphis, craft-handmade, cubism, daniel-clowes, de-stijl, dia-de-muertos, dr-seuss, fantasy-map, futurism, golden-age-comics, googie, ikea-manual, isometric-technical, isotype, jack-kirby, kandinsky, kawaii, keith-haring, knolling, ligne-claire, matsumoto, memphis, moebius, origami, osamu-tezuka, patent-drawing, paul-rand, pixel-art, pop-art-lichtenstein, renaissance-diagram, richard-scarry, rinpa, saul-bass, shan-shui, storybook-watercolor, studio-ghibli, subway-map, sumi-e, superflat, synthwave, technical-schematic, tibetan-thangka, treasure-map, ukiyo-e

Available Layouts

bento-grid, binary-comparison, bridge, circular-flow, comic-strip, comparison-matrix, dashboard, funnel, hierarchical-layers, hub-spoke, iceberg, isometric-map, jigsaw, linear-progression, periodic-table, story-mountain, structural-breakdown, tree-branching, venn-diagram, winding-roadmap

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