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 JCodesMore · Agent Tool · ★ 35.3k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is ai-website-cloner-template safe to install? View the security audit →
AI Website Cloner Template A reusable template for reverse-engineering any website and rebuilding it as a pixel-perfect clone using AI coding agents. Recommended: Claude Code with Opus 4.6 for best results — but works with a variety of AI coding agents. Point it at a URL, run , and your AI agent will inspect the site, extract design tokens and assets, write component specs, and dispatch parallel builders to reconstruct every section. Demo Click the image above to watch the full demo on YouTube. Quick Start Clone this repository Install dependencies Start your AI agent — Claude Code recommended: Run the sk
| Stars | 35,345 |
| Forks | 5,166 |
| Language | TypeScript |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 72.0147599671155/100 |
| Last Updated | 2026-09-27 |
| Created | 2026-03-13 |
| Platforms | browser, claude-code, node |
| Est. Tokens | ~15k |
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ai-website-cloner-template is Clone any website with one command using AI coding agents. It is categorized as a Agent Tool with 35.3k GitHub stars.
ai-website-cloner-template is primarily written in TypeScript. It covers topics such as ai, ai-agents, ai-tools.
You can find installation instructions and usage details in the ai-website-cloner-template GitHub repository at github.com/JCodesMore/ai-website-cloner-template. The project has 35.3k stars and 5166 forks, indicating an active community.
ai-website-cloner-template is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to ai-website-cloner-template on Agent Skills Hub include dify, awesome-claude-skills, sim. 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: