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-ascend-case-elemwise-concatgit 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-ascend-case-elemwise-concat)<a href="https://agentmods.dev/skills/wenyi-li/awesome-agent-kernel-skills/triton-ascend-case-elemwise-concat"><img src="https://agentmods.dev/badge/skills/wenyi-li/awesome-agent-kernel-skills/triton-ascend-case-elemwise-concat/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-ascend-case-elemwise-concat"><img src="https://agentmods.dev/badge/skills/wenyi-li/awesome-agent-kernel-skills/triton-ascend-case-elemwise-concat.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 | $0.00073 | $0.00880 |
| Opus 5 | $0.00036 | $0.00440 |
| Sonnet 5 | $0.00015 | $0.00176 |
| Haiku 4.5 | $0.00007 | $0.00088 |
Grade A, and why
triton-ascend-case-elemwise-concat 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 12d 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.
- 12d ago First seen · 65 lines · 73 tokens per session scan A 763157736a1c
triton-ascend-case-elemwise-concat 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 73 tokens to every session and 880 once invoked, about $0.0004 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 2026-08-31.
Other skills, from other repositories
triton-ascend-case-reduction-amin-atomic
A Triton optimization guide for minimum-value reduction when the reduced dimension is much larger than the other dimension. It uses multiple cores and atomic operations, which combine partial results safely, for extreme shapes such as 16 by 262,144.
triton-ascend-case-matmul-large-k
An optimization guide for matrix multiplication where the shared dimension K is much larger than the output dimensions M and N. It splits the K dimension so multiple processor cores can calculate parts of the same output.
triton-ascend-case-index-histogram
An optimization pattern for histogram counting, which records how often each value appears. It sorts the input first, then uses binary search to find each value's range.
triton-ascend-case-matmul-swizzle2d
An optimization guide for Triton matrix-multiplication kernels on Ascend processors. Matrix multiplication combines rows and columns of two number grids to produce a third grid.
triton-ascend-case-elemwise-broadcast-2d
An optimization pattern for dividing a 2D tensor by values broadcast across rows or columns. It keeps small dimensions together and controls how many processing blocks handle the larger dimension.
triton-ascend-case-elemwise-broadcast-3d
An optimization pattern for 3D broadcast division, where one tensor's values are repeated across selected dimensions. It first expands the repeated values and then reshapes the work into a simpler 2D form.