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 mindspore-ai/akg --skill triton-ascend-case-reduction-mean-largegit clone --depth 1 https://github.com/mindspore-ai/akgWrote 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/mindspore-ai/akg/triton-ascend-case-reduction-mean-large)<a href="https://agentmods.dev/skills/mindspore-ai/akg/triton-ascend-case-reduction-mean-large"><img src="https://agentmods.dev/badge/skills/mindspore-ai/akg/triton-ascend-case-reduction-mean-large/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/mindspore-ai/akg/triton-ascend-case-reduction-mean-large"><img src="https://agentmods.dev/badge/skills/mindspore-ai/akg/triton-ascend-case-reduction-mean-large.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00097 | $0.00573 |
| Opus 5 | $0.00048 | $0.00287 |
| Sonnet 5 | $0.00019 | $0.00115 |
| Haiku 4.5 | $0.00010 | $0.00057 |
Grade A, and why
triton-ascend-case-reduction-mean-large 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 9d 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.
What it actually says
大规模 Mean 归约优化（行二次切分）
任务特征
- 数据尺寸：(1000, 8192)，非reduce轴中等，reduce轴较大
优化：行二次切分
pid = tl.program_id(0)
for m_start in range(0, BLOCK_SIZE_M, SUB_BLOCK_SIZE_M):
m_offsets = pid * BLOCK_SIZE_M + m_start + tl.arange(0, SUB_BLOCK_SIZE_M)
目的：
- 每个kernel计算多行（BLOCK_SIZE_M），减少总线程块数量
- Kernel内对行进行二次切分（SUB_BLOCK_SIZE_M），避免超出硬件缓存
Autotune 配置
# （AI core=40）
# 1. grid<40 -> 28.64 us
triton.Config({'BLOCK_SIZE_M': 50, 'SUB_BLOCK_SIZE_M': 25, 'BLOCK_SIZE_N': 512})
# 2. grid=40，SUB切分含尾块 -> 16.54 us
triton.Config({'BLOCK_SIZE_M': 25, 'SUB_BLOCK_SIZE_M': 4, 'BLOCK_SIZE_N': 4096})
# 3. grid=40，SUB切分不含尾块 -> 16.00 us 最优
triton.Config({'BLOCK_SIZE_M': 25, 'SUB_BLOCK_SIZE_M': 25, 'BLOCK_SIZE_N': 512})
# 4. grid>40，且非核数整数倍 -> 25.86 us
triton.Config({'BLOCK_SIZE_M': 20, 'SUB_BLOCK_SIZE_M': 20, 'BLOCK_SIZE_N': 512})
总结
- grid等于核数，SUB切分不含尾块时性能最优
- 尾块计算会降低性能
- grid超出核数且非核数整数倍时，各核计算任务不均匀，性能较差
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.
- 9d ago First seen · 50 lines · 97 tokens per session scan A a0ce3a89be1c
triton-ascend-case-reduction-mean-large is a skill published in the GitHub repository mindspore-ai/akg (259 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 97 tokens to every session and 573 once invoked, about $0.0005 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.
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