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 loulanyue · Codex Skill · ★ 337
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is spec-kit-zh safe to install? View the security audit →
🌱 Spec Kit ZH 更快地构建高质量软件。 一个开源工具包，让你专注于产品场景与可预期的结果，而不是从零开始凭感觉拼凑每一个实现细节。 目录 🤔 什么是规范驱动开发？ ⚡ 快速开始 📽️ 视频概览 🚶 社区演练项目 🤖 支持的 AI 代理 🔧 specify-zh 命令参考 📚 核心理念 🌟 开发阶段 🎯 实验目标 [🔧 前置要求](#pre
| Stars | 337 |
| Forks | 26 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 63.2165908660454/100 |
| Open Issues | 23 |
| Last Updated | 2026-09-01 |
| Created | 2026-03-17 |
| Platforms | claude-code, codex, python |
| Est. Tokens | ~21k |
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spec-kit-zh is Chinese-localized spec-driven development toolkit for Codex, Claude Code, Cursor, and other AI coding agents.. It is categorized as a Codex Skill with 337 GitHub stars.
spec-kit-zh is primarily written in Python. It covers topics such as ai-coding, chinese, claude-code.
You can find installation instructions and usage details in the spec-kit-zh GitHub repository at github.com/loulanyue/spec-kit-zh. The project has 337 stars and 26 forks, indicating an active community.
spec-kit-zh is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to spec-kit-zh on Agent Skills Hub include quint-code, Aegis, Overture. 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: