xhs-writer-skill: 小红书爆款笔记生成器，基于gpt-image-2，强力超快生成，自然语言修改，超好用

by JuneYaooo · AI Tool · ★ 157

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install xhs-writer-skill

git clone https://github.com/JuneYaooo/xhs-writer-skill.git

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 64/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

claude-code-skillsxhs-skillxhs-writerxiaohongshu-skills

Quick Facts

Stars157
Forks19
LanguagePython
CategoryAI Tool
LicenseApache-2.0
Quality Score64/100
Last Updated2026-04-25
Created2026-04-24
Platformsclaude-code, python
Est. Tokens~14k

About xhs-writer-skill

xhs-writer-skill 小红书爆款笔记生成器 — 从主题到发布，一条龙。 Claude Code / OpenClaw Skill。装进 agent 后，用一句自然语言生成 9:16 竖版卡片组（图文）或短视频脚本，配 caption + hashtags，按规范落盘。支持真实素材图生图、卖点分析、5种标题公式。 🎬 效果演示：真实案例 案例：推广 gpt-image2-ppt-skills 开源项目 输入：GitHub 项目原图 输出：小红书风格卡片（9:16 竖版） GitHub 项目截图（原始素材） 卡片2：对比图（图生图）保留真实对比效果 + 小红书风格文字 GitHub 项目截图（10种风格展示） 卡片3：风格展示（图生图）保留真实素材 + 素人感设计 完整案例： 输入：GitHub 项目链接 + 项目截图素材 流程： 扫描项目素材（README...

Compatible Skills

These tools work well together with xhs-writer-skill for enhanced workflows:

  • skills — semantic(0.20)+complementary+shared_fw(anthropic,openai)+same_lang+similar_pop+shared_platform (73%)
  • claude-skills — semantic(0.18)+complementary+shared_fw(anthropic,openai)+same_lang+similar_pop+shared_platform (72%)
  • claude-code-vision-skill — semantic(0.18)+complementary+shared_fw(anthropic,openai)+same_lang+similar_pop+shared_platform (72%)
  • image-gen-mcp — semantic(0.17)+complementary+shared_fw(anthropic,openai)+same_lang+similar_pop+shared_platform (72%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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:

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