skills/tyrealq/q-skills/q-infographics

q-infographics

SKILL.md

Q-Infographics

Q-Infographics transforms source documents into business stories and infographic images using the Gemini API.

Powered by: google-genai (Nano Banana).

Folder Structure

skills/q-infographics/
|-- SKILL.md           # This file
|-- requirements.txt   # Python dependencies
|-- assets/
|   `-- Logo_Q.png     # Brand logo, auto-overlaid on infographics
|-- prompts/
|   |-- story.txt      # Story generation prompt
|   `-- image.txt      # Infographic generation prompt
|-- scripts/
|   |-- gen_story.py   # Story generator script
|   `-- gen_image.py   # Image generator script

Dependencies

google-genai
Pillow
markitdown

Install: pip install google-genai Pillow markitdown

Script Directory

Agent execution instructions:

  1. Determine this SKILL.md file's directory path as SKILL_DIR.
  2. Script path = ${SKILL_DIR}/scripts/<script-name>.
  3. Prompt path = ${SKILL_DIR}/prompts/<prompt-name>.
Resource Purpose
scripts/gen_story.py Generate business story from document via Gemini API
scripts/gen_image.py Generate infographic image from story via Gemini API
prompts/story.txt Story generation prompt template
prompts/image.txt Infographic generation prompt template

When to Use

Use this skill when the user wants to:

  • Convert a document, report, or text into a compelling business story
  • Create an infographic from written content
  • Transform dry business information into visual summaries
  • Generate cartoon-style visual representations of key points

Workflow

IMPORTANT: After each step, display outputs and ask for user confirmation before proceeding.

Step 1: Prepare Input

Convert the source document to markdown/text.

markitdown <input_file> -o <OUTPUT.md>

Review checkpoint: Show the first ~50 lines of converted content. Ask user to confirm before proceeding.

Step 2: Generate Story

python "${SKILL_DIR}/scripts/gen_story.py" <INPUT.md> "${SKILL_DIR}/prompts/story.txt" > STORY_OUTPUT.md

Review checkpoint:

  1. Show the prompt being used: cat "${SKILL_DIR}/prompts/story.txt"
  2. After generation, show the full story output: cat STORY_OUTPUT.md
  3. Ask user: "Story generated. Review above and confirm to proceed with infographic generation, or request edits."

Step 3: Generate Infographic

python "${SKILL_DIR}/scripts/gen_image.py" STORY_OUTPUT.md "${SKILL_DIR}/prompts/image.txt" <SOURCE_NAME>_INFO

Naming convention: Output files use the source filename with _INFO suffix (e.g., MY_REPORT.pdf -> MY_REPORT_INFO.jpg).

Review checkpoint:

  1. Show the image prompt being used: cat "${SKILL_DIR}/prompts/image.txt"
  2. After generation, display the infographic image
  3. Ask user: "Infographic generated. Would you like to regenerate with different settings?"

Requirements

  • pip install -r "${SKILL_DIR}/requirements.txt"
  • GEMINI_API_KEY environment variable. Load from a .env file: PowerShell (Windows):
    $env:GEMINI_API_KEY = (Get-Content path\to\.env | Where-Object { $_ -match '^GEMINI_API_KEY=' } | Select-Object -First 1).Split('=',2)[1]
    
    Bash (macOS/Linux):
    export $(cat /path/to/.env | xargs)
    

Branding

Every generated infographic is automatically branded with a logo in the bottom-right corner, resized to ~6% of the image width. To use your own logo, place it in the assets/ folder and update LOGO_FILENAME in scripts/gen_image.py.

Customization

  • Story Style: Edit ${SKILL_DIR}/prompts/story.txt to change the writing persona
  • Infographic Style: Edit ${SKILL_DIR}/prompts/image.txt to change the visual art style

Prompts Reference

Story Prompt (prompts/story.txt)

Creates business stories in the style of top-tier Chinese tech media (36Kr, Huxiu). Key elements:

  • Story-first approach with hero's journey structure
  • "Golden sentences" - bold, shareable quotes
  • Effective analogies for complex concepts
  • Structured methodology breakdowns
  • Rhythmic flow with rhetorical questions

Image Prompt (prompts/image.txt)

Generates hand-drawn cartoon-style infographics:

  • 16:9 landscape composition
  • Concise cartoon elements and icons
  • Highlights keywords and core concepts
  • Ample white space for readability
  • Language matches input content
Weekly Installs
36
GitHub Stars
9
First Seen
Feb 2, 2026
Installed on
codex34
gemini-cli33
claude-code33
opencode33
cursor32
github-copilot31