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 Pan-Chera · Agent Tool · ★ 955
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is Multi-Agent-CAD safe to install? View the security audit →
🛠️ MAC (Multi-Agent CAD): Generate printable 3D models with 1% the tokens Tsinghua University · IEI Lab 4 agents collaborating · 116× fewer tokens · 99.3% feature pass rate — turn concise natural language directly into printable 3D models. Same CAD generation capability, 1/116 the tokens, 1/13 the inference cost. 🎬 Web UI walkthrough Below is a screen recording of one full pipeline run through the Web UI. 📖 Table of Contents 📸 Real-World Gallery 🚀 Quick Start 💡 Introduction [4. ✨ Core Features](#4-core-f
| Stars | 955 |
| Forks | 87 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 70.8476761888155/100 |
| Open Issues | 1 |
| Last Updated | 2026-09-16 |
| Created | 2026-07-30 |
| Platforms | python |
| Est. Tokens | ~19k |
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Multi-Agent-CAD is MAC (Multi-Agent CAD): A decoupled multi-agent framework for text-to-CAD generation via constrained test-time compute. It is categorized as a Agent Tool with 955 GitHub stars.
Multi-Agent-CAD is primarily written in Python. It covers topics such as 3d-modeling, 3d-printing, agent-pipeline.
You can find installation instructions and usage details in the Multi-Agent-CAD GitHub repository at github.com/Pan-Chera/Multi-Agent-CAD. The project has 955 stars and 87 forks, indicating an active community.
Multi-Agent-CAD is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to Multi-Agent-CAD on Agent Skills Hub include helix, partmode, step.parts. 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: