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 wenyi-li/awesome-agent-kernel-skills --skill triton-cuda-reducegit clone --depth 1 https://github.com/wenyi-li/awesome-agent-kernel-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/wenyi-li/awesome-agent-kernel-skills/triton-cuda-reduce)<a href="https://agentmods.dev/skills/wenyi-li/awesome-agent-kernel-skills/triton-cuda-reduce"><img src="https://agentmods.dev/badge/skills/wenyi-li/awesome-agent-kernel-skills/triton-cuda-reduce/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/wenyi-li/awesome-agent-kernel-skills/triton-cuda-reduce"><img src="https://agentmods.dev/badge/skills/wenyi-li/awesome-agent-kernel-skills/triton-cuda-reduce.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 | $0.00068 | $0.02607 |
| Opus 5 | $0.00034 | $0.01303 |
| Sonnet 5 | $0.00014 | $0.00521 |
| Haiku 4.5 | $0.00007 | $0.00261 |
Grade A, and why
triton-cuda-reduce 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 8d 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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.
- 8d ago First seen · 296 lines · 68 tokens per session scan A 5229aceee178
triton-cuda-reduce is a skill published in the GitHub repository wenyi-li/awesome-agent-kernel-skills (9 stars, last pushed 3mo ago), with no licence file. It adds 68 tokens to every session and 2,607 once invoked, about $0.0003 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 2026-09-03.
Other skills, from other repositories
triton-cuda-attention
An implementation guide for attention, the Transformer operation that compares queries with keys and combines their values. It covers Flash Attention, which processes attention in blocks instead of storing the full sequence-by-sequence matrix.
triton-cuda-debugging
A troubleshooting checklist for Triton CUDA kernels, covering compilation failures, runtime errors, incorrect results, and performance problems. It includes checks for memory bounds, indexing, shapes, concurrency, and launch settings.
triton-cuda-matmul
A guide to speeding up matrix multiplication, including ordinary, batched, and linear-layer operations, on CUDA GPUs. It covers tiling, shared-memory caching, and Tensor Cores, specialized GPU units for matrix calculations.
triton-cuda-reduce
A guide to reducing many values into one result on a GPU, such as a sum, average, maximum, softmax, or layer normalization. It covers block-level reduction and numerical-stability techniques.
tilelang-cuda-memory
A guide to improving how TileLang CUDA kernels move data through GPU memory. It covers shared memory, registers, local storage, data layouts, combined memory access, and avoiding bank conflicts, where threads compete for the same memory bank.
triton-cuda-elementwise
A guide to implementing and optimizing operations that process tensor elements independently, such as addition, multiplication, activation functions, and mathematical functions. It includes vectorized access and operation fusion patterns.