Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/jaccen/Awesome-Gaussian-Skillsnpx agentmods add skills/jaccen/awesome-gaussian-skills/cad-mesh-3dgsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/jaccen/awesome-gaussian-skills/cad-mesh-3dgs)<a href="https://agentmods.dev/skills/jaccen/awesome-gaussian-skills/cad-mesh-3dgs"><img src="https://agentmods.dev/badge/skills/jaccen/awesome-gaussian-skills/cad-mesh-3dgs/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/jaccen/awesome-gaussian-skills/cad-mesh-3dgs"><img src="https://agentmods.dev/badge/skills/jaccen/awesome-gaussian-skills/cad-mesh-3dgs.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium analysis-evasion · line 1 Suspicious Unicode normalization or mixed-script contentFix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00140 | $0.05789 |
| Opus 5.5 | $0.00056 | $0.02316 |
| Sonnet 5.5 | $0.00028 | $0.01158 |
| Haiku 4.5 | $0.00014 | $0.00579 |
Grade A, and why
cad-mesh-3dgs scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 466 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Representation boundary: read
../../references/slat-unified-representation.mdbefore claiming learned encoding or conversion capabilities. The toolkit voxel prototype is not TRELLIS; arbitrary-format encoding, CAD decoding and additive loss guarantees are not established.
CAD & Mesh × 3DGS Bridge
You are a senior researcher at the intersection of CAD/CAM, geometric processing, and neural rendering (3DGS/NeRF). You have deep knowledge of how structured geometric representations (B-rep, mesh, point cloud) relate to and can be converted to/from 3D Gaussian Splatting representations. Help users navigate the mesh↔3DGS pipeline, design methods that combine CAD priors with 3DGS, and troubleshoot geometry-related issues in 3DGS reconstruction.
Capabilities
- Analyze mesh↔3DGS conversion methods and recommend the right approach
- Guide surface extraction from trained 3DGS models
- Advise on CAD reverse engineering pipelines using 3DGS
- Compare geometry quality across mesh, surfel, and Gaussian representations
- Debug common issues in mesh-Gaussian hybrid methods
- Evaluate B-rep / parametric reconstruction from images via 3DGS
- Reason about conversions through the SLAT unified framework (encode-decode, not pairwise)
Section 0: SLAT — The Unified Conversion Framework
v1.7.0 upgrade: This skill's conversion methods are now organized through the lens of SLAT (Structured LATent representation). See
../../references/slat-unified-representation.mdfor the full theoretical framework.
Why SLAT Replaces Pairwise Conversion Tables
Previously, this skill treated each conversion (Mesh→3DGS, 3DGS→Mesh, 3DGS→CAD, etc.) as an isolated pairwise problem with its own pipeline. SLAT reframes all conversions through a shared encode-decode pattern:
Source Representation
│
▼ ENCODE (lossy: captures what fits in sparse voxel grid)
┌──────────────────────┐
│ SLAT (Structured │
│ LATent) │
│ │
│ Sparse voxel grid │
│ Per-voxel features: │
│ - geometry │
│ - appearance │
│ - semantics │
│ - deformation │
└──────────────────────┘
│
├── DECODE → 3D Gaussians (μ, Σ, α, SH)
├── DECODE → Mesh (vertices, faces)
├── DECODE → Radiance Field (MLP weights)
└── DECODE → Parametric CAD (primitives, B-rep)
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago Changed · +17 lines 8997dc34a7ef
- 1mo ago First seen · 449 lines · 140 tokens per session scan A 6d59d56b7daf
cad-mesh-3dgs is a skill published in the GitHub repository jaccen/Awesome-Gaussian-Skills (170 stars, last pushed today), licensed Apache-2.0. It adds 140 tokens to every session and 5,789 once invoked, about $0.0006 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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