xhs-imagen: Skill for popular science image content creation on Xiaohongshu

by NimaChu · Codex Skill · ★ 120

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

How to install xhs-imagen

git clone https://github.com/NimaChu/xhs-imagen.git

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 60/100

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.

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.

agent-workflowarticle-to-imageinfographic-generatorknowledge-cardslocal-image-generationopenclawsvg-rendererxiaohongshu

Quick Facts

Stars120
Forks4
LanguagePython
CategoryCodex Skill
LicenseMIT
Quality Score60/100
Open Issues2
Last Updated2026-07-28
Created2026-03-29
Platformspython
Est. Tokens~13k

About xhs-imagen

xhs-imagen English 输入一个主题,生成一套可发布的小红书图文:调研、文案、分镜、角色一致性生图、发布前 QA,一次完成。 是一个跨 Agent 的小红书图文生成技能。它不只负责“写一段生图 Prompt”,而是把内容准确性、移动端阅读体验、系列叙事、角色一致性和成品检查放进同一条工作流。 Claude Code、OpenCode、OpenClaw、Hermes、Codex,以及其他能够读取 并调用本地脚本或生图工具的 Agent 都可以使用。 能做什么 从主题、文章、文档或粗略想法开始,先调研并核验事实 生成小红书标题、正文、标签和完整图文叙事 用“认知锚点”筛选值得独立成页的内容,而不是机械分页 为每页设计原创视觉隐喻,让角色真正参与核心动作 自动生成 3:4 封面和 9:16 内页 在 6 套绑定角色与画风的 中选择 有生图工具时优先调用模型;没有时使用本地 SVG...

Compatible Skills

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

  • chubbyskills — semantic(0.20)+complementary+rare_topics+same_lang+similar_pop+shared_platform (61%)

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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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