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-amax-mediumgit 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-amax-medium)<a href="https://agentmods.dev/skills/mindspore-ai/akg/triton-ascend-case-reduction-amax-medium"><img src="https://agentmods.dev/badge/skills/mindspore-ai/akg/triton-ascend-case-reduction-amax-medium/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-amax-medium"><img src="https://agentmods.dev/badge/skills/mindspore-ai/akg/triton-ascend-case-reduction-amax-medium.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 | $0.00081 | $0.00512 |
| Opus 5 | $0.00041 | $0.00256 |
| Sonnet 5 | $0.00016 | $0.00102 |
| Haiku 4.5 | $0.00008 | $0.00051 |
Grade A, and why
triton-ascend-case-reduction-amax-medium 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.
What it actually says
中等规模 Amax 归约优化
任务特征
- 数据尺寸：(2048, 8192)，非reduce轴中等，reduce轴较大
优化 1：计算重组
# 错误：简单方式：循环内多次归约
row_max = -float('inf')
for n_offset in range(0, N, BLOCK_SIZE):
curr_max = tl.max(data_block, 1)
row_max = tl.maximum(curr_max, row_max)
# 正确：优化方式：维护矩阵结构，循环外归约
curr_max = tl.full((BLOCK_SIZE_M, BLOCK_SIZE_N), -float('inf'), dtype=tl.float32)
for n_start in range(0, N, BLOCK_SIZE_N):
curr_max = tl.maximum(data_block, curr_max)
row_max = tl.max(curr_max, 1)
优化 2：Grid 配置
# （AI core=40）
# 1. grid=32<40, UB用满 -> 29.05 us
triton.Config({'BLOCK_SIZE_M': 64, 'BLOCK_SIZE_N': 256})
# 2. grid>40, UB用满 -> 29.09 us
triton.Config({'BLOCK_SIZE_M': 32, 'BLOCK_SIZE_N': 512})
# 3. grid=40, UB不超出 -> 25.73 us 最优
triton.Config({'BLOCK_SIZE_M': 52, 'BLOCK_SIZE_N': 256})
总结
- 计算重组：将多次归约合并为一次，减少归约次数
- Grid配置：grid等于核数时性能最优，需确保UB不超出
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 · 50 lines · 81 tokens per session scan A 3f582d4d7c3c
triton-ascend-case-reduction-amax-medium is a skill published in the GitHub repository mindspore-ai/akg (259 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 81 tokens to every session and 512 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 2026-08-30.
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