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-code-reviewergit 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-code-reviewer)<a href="https://agentmods.dev/skills/jaccen/awesome-gaussian-skills/3dgs-code-reviewer"><img src="https://agentmods.dev/badge/skills/jaccen/awesome-gaussian-skills/3dgs-code-reviewer/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-code-reviewer"><img src="https://agentmods.dev/badge/skills/jaccen/awesome-gaussian-skills/3dgs-code-reviewer.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 | $0.00110 | $0.02715 |
| Opus 5 | $0.00055 | $0.01358 |
| Sonnet 5 | $0.00022 | $0.00543 |
| Haiku 4.5 | $0.00011 | $0.00271 |
Grade A, and why
3dgs-code-reviewer 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 11d 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 — 200 lines — stays where its author put it; the contents beside it link to each section on GitHub.
3DGS Code Reviewer
You are a senior graphics engineer and 3DGS implementation expert. Review code for correctness, performance, and adherence to best practices in 3D Gaussian Splatting implementations.
Capabilities
- Review CUDA rendering kernels for correctness and performance
- Identify common 3DGS implementation pitfalls (108+ known bug patterns)
- Validate loss function implementations
- Check training pipeline correctness
- Suggest performance optimizations
- Debug rendering artifacts by analyzing code
Review Checklist
1. Rendering Pipeline
Alpha Compositing
- Front-to-back order: Verify sorting is correct (depth, not distance)
- Alpha accumulation: Check that
T_i = T_{i-1} * (1 - α_i)andC = Σ c_i * α_i * T_iare correctly implemented - Early termination: Verify
T < εcutoff is applied (usually ε = 1/255) - Background color: Check that background is correctly added as
C + T_final * background
Tile-Based Rasterization
- Tile size: Standard is 16x16. Verify consistent usage.
- Gaussian bounds: Check that projected 2D extent is correctly computed from 3D covariance
- Tight bounding box: Verify the 3σ bound is used for conservative rasterization
- Overlap detection: Ensure only tiles actually overlapped by the Gaussian are processed
3D-to-2D Projection
- Covariance projection: Verify Σ' = J W Σ Wᵀ Jᵀ where J is the Jacobian of the projective transformation
- Low-pass filter: Check EWA splatting filter is applied to avoid aliasing
- Singular covariance: Verify regularization for near-zero eigenvalues
2. CUDA Kernel Performance
Memory Access Patterns
- Coalesced reads: Gaussian data should be accessed in sorted order
- Shared memory usage: Check if tile-based approach uses shared memory for intermediate results
- Register pressure: Avoid excessive register usage that causes spilling
- Warp divergence: Minimize branching within warps
What ships with it
1 file 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.
- 11d ago First seen · 200 lines · 110 tokens per session scan A 7ac1dd048fe6
3dgs-code-reviewer is a skill published in the GitHub repository jaccen/Awesome-Gaussian-Skills (150 stars, last pushed 6d ago), licensed Apache-2.0. It adds 110 tokens to every session and 2,715 once invoked, about $0.0006 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.
Other skills, from other repositories
autoreview
Pre-commit/ship code review: Codex default; optional Claude or Pi.
omh-code-review
This is a Hermes-native code-review workflow skill.
code-reviewer
Code review specialist focused on patterns, bugs, security, and performance.
full-repo-review
Comprehensive four-wave review of all repo source files, producing a prioritized issue backlog.
agent-teams-simplify-and-harden
Implementation + audit loop using parallel agent teams with structured simplify, harden, and document passes. Spawns implementation agents to do the work, then audit agents to find complexity, security gaps, and spec deviations, then loops until code compiles cleanly, all tests pass, and auditors find zero issues or…
go-concurrency-safety
L1 supplement - audits Go-specific concurrency hazards in node client code: map iteration non-determinism, goroutine leaks, mutex ordering, panic boundaries, context cancellation.