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 crawfordxx · Claude Skill · ★ 574
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is xiaoma-durex-copywriter safe to install? View the security audit →
xiaoma-durex-copywriter 一个 Claude Code / Claude.ai Skill。用杜蕾斯黄金期（2011–2017，环时互动操盘）那套「双层语义 + 留白」的方法，产出文案与海报。 这套方法能迁移的东西，是一套制造「我懂了」瞬间的机制。污只是杜蕾斯所在品类的表层材料，把材料换成 AI 课程、职场、理财、健身，机制照样成立。 双层语义 一句合格的杜蕾斯式文案，必须同时成立于两个语境。 作者只写表层，里层由读者自己跳过去。那一下跳跃产生的快感，就是传播动力。 光大银行出乌龙那天，杜蕾斯发的是「光大是不行的」。刘翔摔倒那次，它把「快」和「持久」摆到一起，表层说的是运动员。中元节它只说了四个字，「今晚早回家」。 点破即死是铁律。 只要在文案里解释了里层，这条就废了。 它会做什么 Skill 触发后走一条交互式流程，不会闷头给你一版就完事。 为什么默认不提问。 模型天然倾向多问，而每轮提问都在消耗用户耐心。用户找你是要东西的，不是来做问卷的。一个带明示假设的具体方案，比三个精准的问题更有用，因为用户看到具体的东西才知道自己想要什么。方案本身就是最好的提问方式。 这条是跑评测跑出来的。第一轮测试里 Skill 只缺一个槽位也照样停下来提问，还自己发明了四个槽位之外的新问题。详见 。 安装 Claude Code 下次启动即可用。触发词：「写个文案」「借势热点」「节日海报」「想句 slogan」「课程怎么推」「像杜蕾斯那样写」。 出图部分按需安装。 bash npm i @napi-rs/canvas # Canvas 排版 pip install playwright # HTML 排版（二选一即可）
| Stars | 574 |
| Forks | 25 |
| Language | Python |
| Category | Claude Skill |
| Quality Score | 61.4864017444321/100 |
| Open Issues | 1 |
| Last Updated | 2026-08-08 |
| Created | 2026-08-04 |
| Platforms | claude-code, python |
| Est. Tokens | ~15k |
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xiaoma-durex-copywriter is 杜蕾斯式文案与海报 Skill for Claude Code —— 双层语义方法论 + 8 个文案公式 + 从 260 张原始海报拆解的视觉系统 + AI 出图/代码排版管线. It is categorized as a Claude Skill with 574 GitHub stars.
xiaoma-durex-copywriter is primarily written in Python. It covers topics such as advertising, chinese-copywriting, claude-code.
You can find installation instructions and usage details in the xiaoma-durex-copywriter GitHub repository at github.com/crawfordxx/xiaoma-durex-copywriter. The project has 574 stars and 25 forks, indicating an active community.
The top alternatives to xiaoma-durex-copywriter on Agent Skills Hub include guizang-yingzao-skill, humanizer-ru, creative-director-skill. 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: