Borrowing it
Nothing to install: this file belongs to jaccen/Awesome-Gaussian-Skills. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/jaccen/Awesome-Gaussian-Skills/main/CLAUDE.mdgit 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/instructions/jaccen/awesome-gaussian-skills/claude-md)<a href="https://agentmods.dev/instructions/jaccen/awesome-gaussian-skills/claude-md"><img src="https://agentmods.dev/badge/instructions/jaccen/awesome-gaussian-skills/claude-md/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/instructions/jaccen/awesome-gaussian-skills/claude-md"><img src="https://agentmods.dev/badge/instructions/jaccen/awesome-gaussian-skills/claude-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.04890 | $0.04890 |
| Opus 5 | $0.02445 | $0.02445 |
| Sonnet 5 | $0.00978 | $0.00978 |
| Haiku 4.5 | $0.00489 | $0.00489 |
Grade A, and why
Awesome-Gaussian-Skills CLAUDE.md 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 7d 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 — 221 lines — stays where its author put it; the contents beside it link to each section on GitHub.
name: awesome-gaussian-skills version: "0.8.3" description: "3D Spatial Intelligence Open-Source Toolbox for 3D Gaussian Splatting Research. 819+ methods knowledge base, 15 research-grade skills (3 Router architecture), interactive explorer. Covers 3DGS paper reading, method comparison, code review, experiment planning, CAD/Mesh bridge, visualization, NeRF migration, engineering deployment, CG paper writing, IP generation, spatial intelligence, MCP rendering (spec-first sculpting + code-first export), articulated reasoning, compression & deployment, training debugging. SLAT unified representation framework for conversion skills." when_to_use: "3DGS, Gaussian Splatting, NeRF, 3D reconstruction, surface reconstruction, CAD, mesh, point cloud, novel view synthesis, spatial intelligence, 3D Gaussian, splatting rendering, differentiable rendering, Gaussian world model, procedural 3D, event camera simulation, geometry opacity, reflective material, mesh generation, symmetry 3D generation, spatial control, physics simulation, articulated object, 4D reconstruction, relational language Gaussian, representation abstraction, elastic deformation, DoG pruning, proxy mesh occlusion, test-time spatial training, neuro-symbolic spatial reasoning, interactable digital twin, Bayesian density control, MoE deformation, surgical SLAM, training-free semantic compression, deformable aggregation, PBR material splatting, 3DGS provenance analysis" arguments: [task] author: jaccen license: Apache-2.0 repository: https://github.com/jaccen/Awesome-Gaussian-Skills keywords: ["3dgs", "gaussian-splatting", "spatial-intelligence", "cad", "mesh", "nerf", "3d-reconstruction", "differentiable-rendering", "agent-skills", "mcp"]---
Awesome Gaussian Skills — Project Context
This project is the most comprehensive catalog and AI Agent skill pack for 3D Gaussian Splatting (3DGS) research, covering 819+ methods across 23 categories with 104 known bug patterns.
Anthropic Skills Standard Alignment: This project follows the SKILL.md standard format compatible with Claude Code (
.claude/), Cursor (.cursor/rules/), and other AI Agent frameworks. Each skill includes YAML frontmatter (name, description, version, when_to_use, tags) and structured Markdown body with capabilities, instructions, and reference data. Target:anthropics/skillsofficial repository listing.
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.
- 7d ago Changed · -1 lines · +9 tokens per session 1e7f7d4a5c0e
- 8d ago Changed · +1 lines · +1 tokens per session 2f5163153183
- 12d ago First seen · 221 lines · 4,880 tokens per session scan A d23aa71b0c19
Awesome-Gaussian-Skills CLAUDE.md is an instructions file published in the GitHub repository jaccen/Awesome-Gaussian-Skills (151 stars, last pushed 7d ago), licensed Apache-2.0. It adds 4,890 tokens to every session, about $0.0244 per session on Opus 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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