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 aiworkskills · Claude Skill · ★ 611
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is wechat-article-skills safe to install? View the security audit →
简体中文 | English 微信公众号 AI 运营助手 开源公众号运营数字员工。选好风格，说一句话，AI 自动完成选题、写作、排版、配图到发布的全部流程。不用懂设计，不用会代码。 📚 教程与案例 📖 如何用好 aiworkskills 平台？从配置到发文一文读懂 · 官方使用指南 🔧 WorkBuddy 如何使用 AI Work Skills 运行公众号 · WorkBuddy 组合案例 ⚡ QClaw + aiworkskills 一键运营公众号 · QClaw 组合案例 🔑 小龙虾的模型怎么选 · 写作与配图模型选型指南 🚀 快速开始 能写公众号是一件很简单的事情，把一个公众号写好你一定有独特的见解。 我们开源的skill解决能写能发的问题，可视化配置平台解决你的个性化配置的问题。 推荐路径：在 aiworkskills.cn 可视化配置台选好风格、填完表，一键导出配置包给 AI。 安装技能 1.1 Claw 系列（QClaw / WorkBuddy 等 13+ 工具） 涵盖 QClaw · ArkClaw · JVSCl
| Stars | 611 |
| Forks | 93 |
| Language | Python |
| Category | Claude Skill |
| License | Apache-2.0 |
| Quality Score | 65.5401540207275/100 |
| Open Issues | 1 |
| Last Updated | 2026-09-15 |
| Created | 2026-03-18 |
| Platforms | claude-code, codex, python |
| Est. Tokens | ~15k |
These tools work well together with wechat-article-skills for enhanced workflows:
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wechat-article-skills is 微信公众号 AI 运营助手 | 选题、写稿、审稿、排版、配图、发布全流程 Skill，支持 OpenClaw / Claude Code / Cursor / Codex. It is categorized as a Claude Skill with 611 GitHub stars.
wechat-article-skills is primarily written in Python. It covers topics such as agent-skills, ai-agent, ai-skills.
You can find installation instructions and usage details in the wechat-article-skills GitHub repository at github.com/aiworkskills/wechat-article-skills. The project has 611 stars and 93 forks, indicating an active community.
wechat-article-skills is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to wechat-article-skills on Agent Skills Hub include Overture, ai-skills, humanizer-ru. 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: