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 dacnay816y62-hub · Claude Skill · ★ 54
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is regional-culture-poster safe to install? View the security audit →
Regional Culture Poster FANTASY / 梵想美学 · 文化海报与编辑设计 从地方空间、材料与文化机制出发，设计结构造字海报或地域编辑海报。 快速开始 · 下载与安装 · 完整规则 · 全部视觉 Skills 一分钟开始 生成说明： Skill 组织设计判断、提示词与执行流程；图片由当前环境中可用的图像工具生成或编辑。示例用于理解视觉方向，具体来源以本仓库记录为准，不能据此保证每次得到相同效果。 下载与安装 下载当前分支 ZIP · 阅读 Skill 规则 下载并解压仓库。 将仓库根目录（包含 ）放入当前助手支持的技能目录。 安装文件夹命名为 ，确保入口是 。 在支持技能调用的会话中使用 。如果列表未刷新，新开一个任务。 Codex CLI / IDE 的用户级目录是 ，项目级目录是 ；Windows 用户目录可写为 。以 OpenAI 官方安装说明 为准。ChatGPT 与其他宿主请按各自的技能加载方式使用。 仓库名与调用名可能不同，以上以 中的名称为准。安装不包含图像服务、账户或生成额度；实际出图取决于你使用的环境。 定位 把中国地域文化转译成克制当代的大字海报与编辑海报。它不是旅游宣传模板，不以地标拼贴为核心，也不追求泛化的“国潮风”。 本仓库可作为 Codex skill 或 Claude Code skill 使用。只要宿主支持本地
| Stars | 54 |
| Forks | 9 |
| Language | Python |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 62.4284694329006/100 |
| Last Updated | 2026-09-05 |
| Created | 2026-07-15 |
| Platforms | claude-code, codex, python |
| Est. Tokens | ~14k |
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regional-culture-poster is 把中国地域文化转译成克制当代的大字海报与编辑海报（非旅游宣传）. It is categorized as a Claude Skill with 54 GitHub stars.
regional-culture-poster is primarily written in Python. It covers topics such as ai-art, chinese-culture, claude-skill.
You can find installation instructions and usage details in the regional-culture-poster GitHub repository at github.com/dacnay816y62-hub/regional-culture-poster. The project has 54 stars and 9 forks, indicating an active community.
regional-culture-poster is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to regional-culture-poster on Agent Skills Hub include humanizer-ru, ComfyUI-Agent-Kit, claude-design-auditor-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: