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-index-putgit 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-index-put)<a href="https://agentmods.dev/skills/mindspore-ai/akg/triton-ascend-case-index-put"><img src="https://agentmods.dev/badge/skills/mindspore-ai/akg/triton-ascend-case-index-put/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-index-put"><img src="https://agentmods.dev/badge/skills/mindspore-ai/akg/triton-ascend-case-index-put.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 | $0.00073 | $0.00649 |
| Opus 5 | $0.00036 | $0.00324 |
| Sonnet 5 | $0.00015 | $0.00130 |
| Haiku 4.5 | $0.00007 | $0.00065 |
Grade A, and why
triton-ascend-case-index-put 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
Index Put 索引赋值优化案例
任务特征
- 操作类型：索引赋值，根据索引映射将数据写入目标缓冲区
- 数据尺寸：输入分数(16384, 4)，组缓冲区(8, 65536)
- 特点：不规则内存访问，需逐元素处理以避免写冲突
优化：批量加载 + 数据复用
错误：简单方式：循环内重复加载
for i in tl.range(0, BLOCK_SIZE):
if start_idx + i < total_elements:
# 每次循环都从全局内存加载索引
unit_idx = tl.load(unit_indices_ptr + start_idx + i)
pos_idx = tl.load(position_map_ptr + start_idx + i)
问题：每次循环都访问全局内存，延迟高，效率低。
正确：优化方式：批量加载到UB，循环内复用
# 循环外：批量加载一片索引数据到UB（统一缓冲区）
unit_indices_tile = tl.load(unit_indices_ptr + offsets, mask=mask, other=0)
position_map_tile = tl.load(position_map_ptr + offsets, mask=mask, other=0)
# 循环内：通过get_element从UB中取数，复用数据
for i in tl.range(0, BLOCK_SIZE):
if start_idx + i < total_elements:
# 从UB中取数，避免重复访问全局内存
unit_idx = tl.get_element(unit_indices_tile, [i])
pos_idx = tl.get_element(position_map_tile, [i])
# 后续处理...
优化内容
- 在循环外，通过一次
tl.load操作将整个BLOCK_SIZE的索引数据批量加载到UB - 在循环内，通过
tl.get_element从UB中逐个取出索引值 - 将多次全局内存访问转换为一次批量加载+多次片上缓存访问
- 显著降低内存访问延迟
总结
[通用优化] 当需要在循环中多次访问同一片数据时，应先批量加载到片上缓存（UB），然后通过get_element逐个取用，实现数据复用，减少全局内存访问次数，提升性能。
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 · 57 lines · 73 tokens per session scan A ad962172062c
triton-ascend-case-index-put is a skill published in the GitHub repository mindspore-ai/akg (259 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 73 tokens to every session and 649 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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