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-sum-fusedgit 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-sum-fused)<a href="https://agentmods.dev/skills/mindspore-ai/akg/triton-ascend-case-reduction-sum-fused"><img src="https://agentmods.dev/badge/skills/mindspore-ai/akg/triton-ascend-case-reduction-sum-fused/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-sum-fused"><img src="https://agentmods.dev/badge/skills/mindspore-ai/akg/triton-ascend-case-reduction-sum-fused.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 | $0.00083 | $0.00635 |
| Opus 5 | $0.00042 | $0.00318 |
| Sonnet 5 | $0.00017 | $0.00127 |
| Haiku 4.5 | $0.00008 | $0.00064 |
Grade A, and why
triton-ascend-case-reduction-sum-fused 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
Reduction + Elementwise 融合算子优化
任务特征
- 数据尺寸：(1000, 8192), (8192,)，融合算子
- 特点：先进行向量化逐元素操作，再沿列方向求和归约
优化 1：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)
优化 2：计算重组
# 错误：简单
total_sum = 0.0
for n_offset in range(0, N, BLOCK_SIZE):
total_sum += tl.sum(tl.where(mask, t3, 0.0))
# 正确：优化
acc = tl.zeros([SUB_BLOCK_SIZE_M, BLOCK_SIZE_N], dtype=tl.float32)
for n_start in range(0, N, BLOCK_SIZE_N):
acc += tl.where(mask, t3, 0.0)
total_sum = tl.sum(acc, axis=1)
Autotune 配置
# （AI core=40）
# 1. grid=20<40 -> 91.69 us
triton.Config({'BLOCK_SIZE_M': 50, 'SUB_BLOCK_SIZE_M': 25, 'BLOCK_SIZE_N': 256})
# 2. grid=40，SUB切分含尾块 -> 53.30 us
triton.Config({'BLOCK_SIZE_M': 25, 'SUB_BLOCK_SIZE_M': 4, 'BLOCK_SIZE_N': 2048})
# 3. grid=40，SUB切分不含尾块 -> 47.58 us 最优
triton.Config({'BLOCK_SIZE_M': 25, 'SUB_BLOCK_SIZE_M': 25, 'BLOCK_SIZE_N': 256})
# 4. grid>40，且非核数整数倍 -> 79.00 us
triton.Config({'BLOCK_SIZE_M': 20, 'SUB_BLOCK_SIZE_M': 20, 'BLOCK_SIZE_N': 256})
总结
融合算子优化逻辑以reduce为主。grid等于核数、SUB切分不含尾块时性能最优。
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 · 60 lines · 83 tokens per session scan A cfdf0724aab8
triton-ascend-case-reduction-sum-fused is a skill published in the GitHub repository mindspore-ai/akg (259 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 83 tokens to every session and 635 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 2026-09-03.
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