ascendc-operator-performance-eval

ascendc-operator-performance-eval is an MLOps & model serving skill for AI agents, published by Ascend in the agent-skills repository on GitHub. Skillspace rates ascendc-operator-performance-eval D (66/100) and it passed the safety scan; the rating is based on static analysis only.

在 ascend-kernel 的 csrc/ops/<op>/test 下维护仅含 JSONL 的 profiler 性能用例，使用 torch_npu.profiler（固定 warmup=5、active=5）采集，汇总 ASCEND_PROFILER_OUTPUT/op_statistic.csv 的 Total Time(us)，输出含 DType 列的统一 Markdown 对比报告（自定义算子 vs 标杆）。不生成 perf_cases.json 与 *_profiler_results.json。参考实现见 examples/layer_norm_profiler_reference/。

Grade
D
Quality
66 / 100
Safety
Passed
GitHub stars
27

Unproven: rated by static analysis only, not yet compared head-to-head.

Our two independent classifiers differ on this skill's category, so treat the placement as provisional.

This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.

View source on GitHubAscend/agent-skills

Our review

Architecture
73 / 100
Maturity
Structured: ships references or scripts
Security scan
No issues found
License
MulanPSL-2.0
Adoption
Adopted by 0 other repositories, in 1 collections

Not checked yet

  • Category is a classifier prediction; no model has read this skill yet
  • Not judged on the rubric yet (not a contender in its category)
  • No blind task eval yet
  • Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
  • Sibling files (scripts, references) not fetched; security scan covers SKILL.md only

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