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 tettethu · Codex Skill · ★ 247
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is VibeGame safe to install? View the security audit →
Project Page · Watch Demos · Technical Report · Discord · WeChat Group VibeGame: Vibe Your Dream Game News [2026.08] 🚀 We release VibeGame: Prompt-to-Game Development with AI-Native Engine and Self-Evolving Adversarial Agent Team! Check our Project Page and Technical Report
| Stars | 247 |
| Forks | 14 |
| Language | Python |
| Category | Codex Skill |
| License | Apache-2.0 |
| Quality Score | 56.7924829299475/100 |
| Last Updated | 2026-09-19 |
| Created | 2026-08-12 |
| Platforms | browser, claude-code, codex, python |
| Est. Tokens | ~15k |
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VibeGame is VibeGame: Vibe Your Dream Game -- An open-source self-evolving multi-agent framework with an AI-Native game engine that turns your natural language into a fully playable 2D web game and edit it any wa. It is categorized as a Codex Skill with 247 GitHub stars.
VibeGame is primarily written in Python. It covers topics such as agent, claude-code, codex.
You can find installation instructions and usage details in the VibeGame GitHub repository at github.com/tettethu/VibeGame. The project has 247 stars and 14 forks, indicating an active community.
VibeGame is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to VibeGame on Agent Skills Hub include SWE-AF, mcp-image, weppy-roblox-mcp. 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: