ascend-profiling-analysis
ascend-profiling-analysis is a Model training & evaluation skill for AI agents, published by maoxx241 in the vllm-ascend-workspace repository on GitHub. Skillspace rates ascend-profiling-analysis B (81/100) and it passed the safety scan; the rating is based on static analysis only.
Analyze Ascend NPU torch profiler output (kernel_details.csv / trace_view.json / op_summary / communication.json) for one or many profiling roots and produce a traceable report (rank/step/layer/operator summary, cross-rank alignment, diagnosis findings, report.md / report.xlsx / report.html with single-step inspectors, bubble tracing axes, and zoomable Chrome-tracing-style timelines). Use for requests like "分析 profiling", "解析这份 kernel_details", "看 step/layer 切分", "跨 rank 对齐", "通信慢/EP 不均/快慢卡", "生成 profiling 报告". Do not use for HBM/显存归因 (use ascend-memory-profiling), service lifecycle (use vllm-ascend-serving), benchmarks (use vllm-ascend-benchmark), or采集 profiling 数据 (use ascend-profiling-collection).
- Grade
- B
- Quality
- 81 / 100
- Safety
- Passed
- GitHub stars
- 25
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.
Our review
- Architecture
- 100 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked 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
Skillspace indexes and rates this skill; it does not host or endorse it. Run third-party skills at your own risk.