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 jaccen · Codex Skill · ★ 149
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is Awesome-Gaussian-Skills safe to install? View the security audit →
Awesome Gaussian Skills The Most Comprehensive 3DGS Paper Catalog — 660+ Methods, 25 Categories, Interactive Explorer You shouldn't search 20 different repos for 3DGS papers. This is the only one you need — plus AI-powered tools that no other list has. English | 中文 What's New (June 2026) Latest update (Jun 5): 630+ → 660+ methods, 25 categories, 97+ bug patterns. +18 new methods including: ZipSplat (token-based feed-forward 3DGS, 6x fewer Gaussians, +2.1dB PSNR), Geometry Gaussians (per-splat geometry opacity decoupling), 3DReflecNet (CVPR 2026, systematic benchmark for reflective/transparent 3D reco
| Stars | 149 |
| Forks | 10 |
| Language | TypeScript |
| Category | Codex Skill |
| License | Apache-2.0 |
| Quality Score | 65.4764854274682/100 |
| Open Issues | 1 |
| Last Updated | 2026-09-05 |
| Created | 2026-04-28 |
| Platforms | claude-code, node |
| Est. Tokens | ~25k |
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Awesome-Gaussian-Skills is 图形学与3DGS、空间智能持续更新论文；AI Agent Skills for 3D Gaussian Splatting, NeRF & Computer Graphics Research. 700+ methods, 25categories, 12skills. OpenClaw / Claude Code compatible.. It is categorized as a Codex Skill with 149 GitHub stars.
Awesome-Gaussian-Skills is primarily written in TypeScript. It covers topics such as 3d-gaussian-splatting, 3d-reconstruction, 3dgs.
You can find installation instructions and usage details in the Awesome-Gaussian-Skills GitHub repository at github.com/jaccen/Awesome-Gaussian-Skills. The project has 149 stars and 10 forks, indicating an active community.
Awesome-Gaussian-Skills is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to Awesome-Gaussian-Skills on Agent Skills Hub include Overture, RivalSearchMCP, soul.md. 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: