Verified:GitHub

sn-infographic

Generate infographic visuals with iterative VLM-based review and ranking.

2|Updated May 19, 2026

Search Tags:#data visualization #visual summary #prompt expansion #infographic generation #image quality ranking #VLM review

Ready to run

npx skills add https://github.com/aiyinluya/SenseNova-Skills-Studio --skill sn-infographic-aiyinluya

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: sn-infographic
Source: https://github.com/aiyinluya/SenseNova-Skills-Studio/tree/main/skills/sn-infographic
Command: npx skills add https://github.com/aiyinluya/SenseNova-Skills-Studio --skill sn-infographic-aiyinluya

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill turns your raw idea or information request into a structured, evaluated, and high-quality infographic with an automatically selected layout and visual style.

Core Features & Use Cases

Prompt evaluation & expansion: Assesses prompt quality and expands it (optionally over multiple rounds) to improve image generation reliability.
Content analysis & design planning: Analyzes the request into learning objectives, structured section content, and visual opportunities, while preserving source data verbatim.
Iterative generation with VLM review: Generates multiple infographic candidates, reviews them with a vision model, ranks by quality, and returns the best result for display.
Works with composite workflows: Can be used standalone or composed into end-to-end office/report pipelines.

Quick Start

Ask the AI to generate an infographic by sending your request and setting max_rounds to 1 for a fast single-shot result.

Frequently Asked Questions about sn-infographic

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I generate an infographic from raw text or long-form educational material?▼

To generate an infographic, provide your raw text or information request and the system analyzes content structure, selects a layout, produces multiple image candidates, and returns the highest-ranked visual summary. Set max_rounds to 1 for a fast single-shot result.

How does VLM review improve data visualization quality?▼

VLM review improves data visualization by using a vision language model to evaluate generated infographic candidates, rank them by image quality, and return the best result. This iterative generation and review process ensures publication-ready visual summaries.

Can I use this for creating visual summaries of metrics and process comparisons?▼

Yes, you can create visual summaries for metrics, process comparisons, concepts, and long-form educational material. The system analyzes your request into structured section content and visual opportunities while preserving source data verbatim.

What is the best way to ensure strict verbatim data preservation in infographic generation?▼

To ensure strict verbatim data preservation, the system analyzes input content to extract learning objectives and structured sections without altering the source data. It automatically selects styles from references and generates visual outputs maintaining data accuracy.

Does this infographic generation workflow support prompt expansion for better reliability?▼

Yes, the workflow supports prompt evaluation and expansion. It assesses prompt quality and optionally expands it over multiple rounds to improve image generation reliability before producing the final infographic output.

Can I compose this infographic generation tool into end-to-end office report pipelines?▼

Yes, you can compose this tool into end-to-end office and report pipelines. It works standalone or integrates into composite workflows, utilizing two-tier orchestration with image generation, recognition, and text optimization components.