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 →
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🔒 Is writing-style-skill safe to install? View the security audit →
Writing Style Skill 可复用的写作风格 Skill 模板。内置自动学习 — 从你的修改中自动提取规则，SKILL.md 越用越准。 兼容 Claude Code + OpenClaw (ClawHub)。 原理 只要两个数据点：original（AI 第一版）和 final（你最终版）。中间改了多少轮不管。 安装 快速开始 改 SKILL.md — 把模板里的风格规则改成你自己的（或留空，让自动学习帮你填） 让 AI 用这个 skill 写内容 你改到满意 记录： 提取规则： 文件结构 自动学习怎么工作 记录 AI 原稿和你的最终版 用 LLM 分析 diff，提取写作规则 规则按置信度分 P0/P1/P2，P0 自动应用 每次更新前自动备份，一键回滚 LLM 支持 自动检测： (Claude Code) — 优先 (pip install llm) — 通用 环境变量 — 自定义 零依赖纯 Python。 License MIT
| Stars | 252 |
| Forks | 28 |
| Language | Python |
| Category | AI Tool |
| Quality Score | 53.9924328000047/100 |
| Open Issues | 2 |
| Last Updated | 2026-03-24 |
| Created | 2026-03-24 |
| Platforms | claude-code, python |
| Est. Tokens | ~1k |
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writing-style-skill is Writing style skill template with built-in auto-learning. AI writes → you edit → rules auto-extracted → SKILL.md improves. Works with Claude Code + OpenClaw.. It is categorized as a AI Tool with 252 GitHub stars.
writing-style-skill is primarily written in Python.
You can find installation instructions and usage details in the writing-style-skill GitHub repository at github.com/jzOcb/writing-style-skill. The project has 252 stars and 28 forks, indicating an active community.
The top alternatives to writing-style-skill on Agent Skills Hub include pivotnacci, MedgeClaw, SciToolAgent. 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: