No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by Vivixiao980 · Claude Skill · ★ 169
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is xhs-cover-skill safe to install? View the security audit →
小红书封面生成器 - Codex Skill 在 Codex 中直接生成或修改小红书封面。推荐安装到 Codex，这样可以优先调用 Codex 的 GPT Image 2 / 图片生成能力；Gemini 命令行脚本保留为备用方案。 官网：xhscover.vivi.wiki（可在线预览所有风格效果图） 效果预览 支持 18 种预设风格，覆盖职场、居家、综艺、文艺等各类场景： 在 Codex 中选择风格后，Skill 会自动完成上图中所有配置步骤，直接输出封面图片。 完整风格效果图可在 xhscover.vivi.wiki 预览。 前置要求 Codex（推荐，可直接调用 Codex 的 GPT Image 2 / 图片生成能力） Node.js 18+（仅 Gemini CLI 备用方案和命令行脚本需要，macOS / Linux / Windows 均支持） 安装 Codex（推荐）： 重启 Codex 后，Skill 自动生效。在 Codex 中使用时，默认优先走 Codex 自带的图片生成/编辑能力，不需要先配置 Gemini API。 如果只使用 Codex 主流程， 可以跳过；安装依赖是为了启用 Gemini CLI 备用方案和直接命令行脚本。 Claude Code / Gemini CLI 备用方案： 重启 Claude Code 后，Skill 自动生效。没有 Codex 图片生成能力时，会回落到 Gemini API 命令行流程。 OpenClaw： 然后在 OpenClaw 配置中添加 API Key（可替代 Onboarding 流程）： yaml /.openclaw/config.yaml skills: entries: xhs-cover: env: XHSCOVERAPIKEY: "你的 API Key" XHSCOVERBASEURL: "https://generativelanguage.goo
| Stars | 169 |
| Forks | 14 |
| Language | JavaScript |
| Category | Claude Skill |
| Quality Score | 61.4931582919879/100 |
| Open Issues | 1 |
| Last Updated | 2026-05-26 |
| Created | 2026-04-12 |
| Platforms | claude-code, node |
| Est. Tokens | ~800k |
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xhs-cover-skill is 小红书封面生成器 - Claude Code Skill，支持18种预设风格，命令行直接生成小红书封面. It is categorized as a Claude Skill with 169 GitHub stars.
xhs-cover-skill is primarily written in JavaScript.
You can find installation instructions and usage details in the xhs-cover-skill GitHub repository at github.com/Vivixiao980/xhs-cover-skill. The project has 169 stars and 14 forks, indicating an active community.
The top alternatives to xhs-cover-skill on Agent Skills Hub include digital-marketing-pro, life-sciences, claude-ai-mcp. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: