Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add jaccen/Awesome-Gaussian-Skills --skill 3dgs-visualizergit clone --depth 1 https://github.com/jaccen/Awesome-Gaussian-SkillsWrote 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/3dgs-visualizer)<a href="https://agentmods.dev/skills/jaccen/awesome-gaussian-skills/3dgs-visualizer"><img src="https://agentmods.dev/badge/skills/jaccen/awesome-gaussian-skills/3dgs-visualizer/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/3dgs-visualizer"><img src="https://agentmods.dev/badge/skills/jaccen/awesome-gaussian-skills/3dgs-visualizer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00084 | $0.04373 |
| Opus 5.5 | $0.00034 | $0.01749 |
| Sonnet 5.5 | $0.00017 | $0.00875 |
| Haiku 4.5 | $0.00008 | $0.00437 |
Grade A, and why
3dgs-visualizer 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 — 324 lines — stays where its author put it; the contents beside it link to each section on GitHub.
3DGS Visualizer — Publication-Quality Research Visualizations
Generate publication-quality charts for 3DGS method landscape comparison and evolution tracking.
Capabilities
- Radar Charts: Multi-dimensional method capability comparison
- Comparison Tables: Visual performance/efficiency tables with highlighting
- Method Timelines: Chronological evolution showing trends and paradigm shifts
- Dual Output: Static (PDF/PNG via matplotlib) and interactive HTML (via plotly)
Data Sources
| File | Content |
|---|---|
../../references/3dgs-methods-overview.md |
Master index, metrics summary |
../../references/methods-core.md |
Foundation, Geometry, CAD, Generation, Feed-Forward, Compression, Dynamic |
../../references/methods-semantic-editing.md |
Semantic, Editing, Avatar, Material methods |
../../references/methods-systems-apps.md |
Robustness, Driving, SLAM, Simulation, Cross-Domain |
../../references/baselines.md |
Standard baselines with core metrics |
../../references/experiments.md |
Dataset configs, efficiency reference values |
Visualization 1: Radar Charts (Method Capability Comparison)
When to use: Comparing 3–8 methods across multiple dimensions; showing quality/speed/memory trade-offs; use-case recommendation.
Dimensions
| Dimension | Scoring Criteria (0–10) |
|---|---|
| Render Quality | 10=SOTA, 7=competitive, 5=acceptable, 3=below baseline |
| Render Speed | 10=200+ FPS, 7=60–100, 5=30–60, 3=<30 |
| Memory Efficiency | 10=<50MB, 7=100–500MB, 5=0.5–2GB, 3=>2GB |
| Geometry Quality | 10=mesh-ready (2DGS/SuGaR), 7=decent depth, 5=approx, 3=poor |
| Scalability | 10=city-scale, 7=building, 5=room, 3=object-only |
| Ease of Use | 10=single script, 7=standard pipeline, 5=multi-stage, 3=complex setup |
| Novelty | 10=paradigm shift, 7=significant extension, 5=incremental, 3=minor tweak |
Adjust dimensions by context (compression: add "Compression Ratio"; avatar: add "Expression Fidelity"; SLAM: add "Tracking Accuracy").
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 · +8 lines f7c25df73987
- 7d ago Changed fe61399f59e0
- 13d ago Changed c0820ff730cd
- 1mo ago Changed cecfe94831ca
- 1mo ago Changed 08003f990d1e
- 1mo ago Changed 8fa745206086
- 1mo ago Changed · +1 lines 750be391025e
- 1mo ago First seen · 315 lines · 84 tokens per session scan A 25a33a026bf3
3dgs-visualizer is a skill published in the GitHub repository jaccen/Awesome-Gaussian-Skills (170 stars, last pushed today), licensed Apache-2.0. It adds 84 tokens to every session and 4,373 once invoked, about $0.0003 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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