This project provides a specialized "skill" for the Codex environment designed to generate Xiaohongshu (Little Red Book) cover prompts for AI image generation models. It targets users who need to create visually striking, consistent cover art for content such as tutorials, product reviews, and personal experience articles, offering a streamlined process to achieve a specific, popular aesthetic.

How It Works

The skill employs an interactive, question-driven approach to gather user preferences. It guides users through selecting cover styles, uploading reference images, defining character expressions, choosing background colors, and specifying text and font treatments. Based on these inputs, it applies a set of predefined design rules and 8 distinct visual templates to construct a detailed, ready-to-use prompt optimized for image generation models.

Quick Start & Requirements

• Primary install / run command: Copy the atutun-xhs-cover directory into the Codex skills directory: cp -R atutun-xhs-cover ~/.codex/skills/. Usage is then via $atutun-xhs-cover within Codex or by describing the desired cover.
• Non-default prerequisites and dependencies: Requires the Codex environment. No other specific software, hardware, or API keys are mentioned.
• Links: No direct links to official quick-start guides, demos, or documentation beyond the README content are provided.

Highlighted Details

• Supports 8 distinct Xiaohongshu cover style templates.
• Enforces strict design specifications including a 3:4 aspect ratio, 35-55% subject framing, specific color usage (#FDFFA7 for yellow elements), bold outlined typography, and distinct person cutouts.
• Emphasizes high-contrast, high-density compositions with strong emotional cues for immediate readability.

Maintenance & Community

No information regarding notable contributors, sponsorships, community channels (e.g., Discord, Slack), or a public roadmap is present in the provided README.

Licensing & Compatibility

The README does not specify a software license. This omission makes it impossible to determine compatibility for commercial use, closed-source linking, or other adoption scenarios without further clarification.

Limitations & Caveats

The project is presented as a component within the Codex ecosystem, suggesting it may not function as a standalone tool. The repository explicitly states it does not include local demonstration assets. Most critically, the absence of a license is a significant adoption blocker, preventing clear understanding of usage rights and restrictions. Users are advised to verify that no personal privacy information, sensitive keys, or unauthorized materials are included before public release.