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 github · AI Skill · ★ 139.9k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is spec-kit safe to install? View the security audit →
🌱 Spec Kit Build high-quality software faster. An open source toolkit that allows you to focus on product scenarios and predictable outcomes instead of vibe coding every piece from scratch. Table of Contents 🤔 What is Spec-Driven Development? ⚡ Get Started 📽️ Video Overview 🚶 Community Walkthroughs 🤖 Supported AI Agents 🔧 Specify CLI Reference 🧩 Making Spec Kit Your Own: Extensions & Presets [📚 Core Ph
| Stars | 139,945 |
| Forks | 12,524 |
| Language | Python |
| Category | AI Skill |
| License | MIT |
| Quality Score | 69.3285728747937/100 |
| Open Issues | 269 |
| Last Updated | 2026-10-02 |
| Created | 2025-08-21 |
| Platforms | python |
| Est. Tokens | ~25k |
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spec-kit is 💫 Toolkit to help you get started with SDD or any other process!. It is categorized as a AI Skill with 139.9k GitHub stars.
spec-kit is primarily written in Python. It covers topics such as ai, copilot, development.
You can find installation instructions and usage details in the spec-kit GitHub repository at github.com/github/spec-kit. The project has 139.9k stars and 12524 forks, indicating an active community.
spec-kit is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to spec-kit on Agent Skills Hub include n8n, ui-ux-pro-max-skill, gemini-cli. 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: