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huashu-xhs-image

Generate Xiaohongshu cover images in 3:4 portrait PNGs with HTML fallback.

Updated May 5, 2025
Search Tags:#workflow#ai#visuals#image-generation#xiaohongshu#cover-design
One-click install
npx skills add https://github.com/yopitek/Obsidian --skill huashu-xhs-image-yopitek
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: huashu-xhs-image
Source: https://github.com/yopitek/Obsidian/tree/main/HQ/10_resources/01_AI_Skills/huashu-skills-master/huashu-xhs-image
Command: npx skills add https://github.com/yopitek/Obsidian --skill huashu-xhs-image-yopitek

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires google-genai>=1.0.0, pillow>=10.0.0, httpx[socks], and includes scripts (resource) and references (resource) components.

What problem does it solve?

Generate high-quality Xiaohongshu cover images for notes, streamlining visuals creation and saving time in design iterations.

Core Features & Use Cases

  • Dual-path generation: AI-generated previews plus an HTML-based fallback for typography-accurate variants.
  • 3:4 portrait outputs: Enforces 1080x1440 resolution ideal for Xiaohongshu covers.
  • Batch organization: Structured outputs with clear naming for multi-image campaigns (covers, carousels, and a/b tests).
  • Use Case: Create two design directions for a tutorial post, compare engagement, and select the best variant for publishing.

Quick Start

Generate two design directions for a Xiaohongshu cover prompt, choose one, and render the final PNGs.

Frequently Asked Questions about huashu-xhs-image

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

FAQPage Schema
How do I generate Xiaohongshu cover images with AI for my notes?▼

Generate Xiaohongshu cover images by providing a prompt to the AI renderer. The Skill outputs ready-to-upload 1080x1440 PNG files in a 3:4 portrait ratio, streamlining visual creation and saving design time.

What is the standard image resolution for Xiaohongshu cover design?▼

The standard resolution for Xiaohongshu cover design is 1080x1440 pixels. This Skill enforces a 3:4 portrait aspect ratio to ensure the generated visuals perfectly fit the platform's cover specifications.

Can I generate multiple cover design variants for A/B testing on Xiaohongshu?▼

Yes, you can generate multiple cover design variants for A/B testing. The Skill uses dual-direction generation and batch organization with structured naming to compare engagement across tutorials, product showcases, and personal posts.

Does the Xiaohongshu cover generator support HTML-based fallback for typography?▼

Yes, the Xiaohongshu cover generator supports an HTML-based fallback for typography-accurate variants. This dual-path generation complements AI-rendered previews to ensure precise text layout in the final PNG outputs.

Do I need Python packages like Pillow and google-genai to run the image generation workflow?▼

Yes, the image generation workflow requires Python packages including google-genai, Pillow, and httpx. These dependencies drive the AI rendering and image processing for producing the final Xiaohongshu cover PNGs.

What are the limitations of using AI rendering for Xiaohongshu cover design?▼

AI rendering for Xiaohongshu cover design may lack precise typography control, necessitating the HTML-based fallback. Outputs are strictly locked to the 1080x1440 3:4 portrait ratio for Xiaohongshu platform compliance.

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