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 liangdabiao · AI Tool · ★ 5
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is wechat-article-remotion safe to install? View the security audit →
动画skill: 把任意一篇微信公众号文章 转成 Studio 风格的 Remotion 视频 —— 暖白画布 + 上下镜像透视格子 + 顶部章节进度 + 公众号原文图完整保留
| Stars | 5 |
| Forks | 2 |
| Language | Python |
| Category | AI Tool |
| Quality Score | 58.0595353234172/100 |
| Last Updated | 2026-08-03 |
| Created | 2026-08-02 |
| Platforms | python |
| Est. Tokens | ~17k |
Looking for a wechat-article-remotion alternative? If you're comparing wechat-article-remotion with other ai tool tools, these 4 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
Vendor-neutral MCP configuration manager — one CLI to add, toggle, and audit MCP servers and skills across eve
Agent Skill for generating AGENTS.md files following the agents.md convention | Claude Code compatible
An AI-powered virtual development team of 12 specialized agents that helps you create applications through int
AgentX - Agent Extension: MCP Servers, Agent Skills and Plugins Manager
Explore other popular ai tool tools:
wechat-article-remotion is 动画skill: 把任意一篇微信公众号文章 转成 Studio 风格的 Remotion 视频 —— 暖白画布 + 上下镜像透视格子 + 顶部章节进度 + 公众号原文图完整保留. It is categorized as a AI Tool with 5 GitHub stars.
wechat-article-remotion is primarily written in Python. It covers topics such as skill, skills.
You can find installation instructions and usage details in the wechat-article-remotion GitHub repository at github.com/liangdabiao/wechat-article-remotion. The project has 5 stars and 2 forks, indicating an active community.
The top alternatives to wechat-article-remotion on Agent Skills Hub include mcpick, agent-rules-skill, Dream-Creator. 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: