Skill collection
ZJLi2013/awesome-kernel-skills agent skills
- skills
- 12
- GitHub stars
- 102
- Stars
- 102 (14 forks)
- Licence
- No licence
- Last push
- Mar 2026
- Created
- Mar 2026
Install all skills
npx skills add ZJLi2013/awesome-kernel-skillsAdd --skill <name> for a single skill and -a <agent> to choose the agent (see the agent guides).
Skills in ZJLi2013/awesome-kernel-skills, ranked
Ranked by score. Sort bymost stars,trending,newest,recently updated
| # | Skill | Repository | Stars | Used in | Tokens | Auto-check | Licence | Updated |
|---|---|---|---|---|---|---|---|---|
| 1 | Optimize fused cross-entropy loss kernels in Triton for NVIDIA and AMD GPUs. | ZJLi2013/ | 102 | — | ~461 | Automated safety check: Pass | No licence | 6 mo ago |
| 2 | Optimize FlashAttention-style fused attention kernels in Triton for NVIDIA and AMD GPUs. | ZJLi2013/ | 102 | — | ~697 | Automated safety check: Pass | No licence | 6 mo ago |
| 3 | Optimize Fused Mixture-of-Experts (MoE) kernels in Triton for NVIDIA and AMD GPUs. | ZJLi2013/ | 102 | — | ~699 | Automated safety check: Pass | No licence | 6 mo ago |
| 4 | Optimize dense matrix multiplication (GEMM) kernels in Triton for NVIDIA and AMD GPUs. | ZJLi2013/ | 102 | — | ~1.1k | Automated safety check: Pass | No licence | 6 mo ago |
| 5 | Orchestrates continuous kernel optimization by chaining profiling, bottleneck diagnosis, tier-based optimization, verification, and benchmarking into an iterative loop. | ZJLi2013/ | 102 | — | ~2.5k | Automated safety check: Pass | No licence | 6 mo ago |
| 6 | Unified kernel benchmarking protocol producing JSON results with latency, TFLOPS, GBps, and comparison against PyTorch baselines. | ZJLi2013/ | 102 | — | ~567 | Automated safety check: Pass | No licence | 6 mo ago |
| 7 | Profile GPU kernels using NCU (NVIDIA) or rocprof (AMD) to collect performance metrics. | ZJLi2013/ | 102 | — | ~696 | Automated safety check: Pass | No licence | 6 mo ago |
| 8 | 5-stage kernel correctness verification protocol for Triton and CUDA kernels. | ZJLi2013/ | 102 | — | ~702 | Automated safety check: Pass | No licence | 6 mo ago |
| 9 | Optimize RMS Normalization kernels in Triton for NVIDIA and AMD GPUs. | ZJLi2013/ | 102 | — | ~728 | Automated safety check: Pass | No licence | 6 mo ago |
| 10 | Optimize fused softmax kernels in Triton for NVIDIA and AMD GPUs. | ZJLi2013/ | 102 | — | ~742 | Automated safety check: Pass | No licence | 6 mo ago |
| 11 | Optimize Rotary Position Embedding (RoPE) kernels in Triton for NVIDIA and AMD GPUs. | ZJLi2013/ | 102 | — | ~421 | Automated safety check: Pass | No licence | 6 mo ago |
| 12 | Classifies GPU kernel bottlenecks (memory, compute, latency) from profiling metrics and applies GEAK-style workload guidance: what to prefer, consider, or deprioritize. | ZJLi2013/ | 102 | — | ~992 | Automated safety check: Pass | No licence | 6 mo ago |
Questions, answered from the data.
What is the best skill in ZJLi2013/awesome-kernel-skills?
Cross Entropy Kernel from ZJLi2013/awesome-kernel-skills ranks first of the 12 skills in ZJLi2013/awesome-kernel-skills listed here, with the highest score: its repository has 102 GitHub stars, its SKILL.md loads about 461 tokens and it passes the automated safety check with no findings. Next come Flash Attention Kernel and Fused Moe Kernel.
Are the skills in ZJLi2013/awesome-kernel-skills official?
None yet. All 12 skills in ZJLi2013/awesome-kernel-skills listed here come from community repositories; a skill counts as official when the product's own GitHub organization publishes it.
How do I install all skills from ZJLi2013/awesome-kernel-skills?
Run npx skills add ZJLi2013/awesome-kernel-skills in your project: the open-source skills CLI installs the repository's skills into your coding agent's skills folder. To install a single skill, open its page here for the exact command.
How are these skills ranked?
By Skill Navigator score, which combines the GitHub stars of the skill's repository (shared across that repo's skills and discounted for large collections), how many other GitHub owners carry a copy of the skill, and automated SKILL.md quality checks, minus penalties for safety-check warnings and for each further skill from the same repository. Skills that fail the safety check are not listed.