ai-for-science-ai4s-profiling

ai-for-science-ai4s-profiling is a skill for Claude Code from ascend-ai-coding/awesome-ascend-skills. It costs 93 tokens per session (4,134 once invoked), scanned A, original, no licence file.

A performance-profiling guide for Huawei Ascend NPUs using `torchnpu.profiler`. Profiling records timing, call stacks, memory use, and other measurements so developers can see where training or inference spends time.

In plain words
What is it for?
Collecting performance data at several detail levels, finding slow operations and call paths, examining memory use, and choosing follow-up optimizations.
Why use it?
It helps replace guesswork with measurements when an AI workload is slow. The results can show which operations or memory costs are creating bottlenecks.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the ascend-ai-for-science plugin — 14 skills shipped together , and of ai-for-science

Good fit Collecting performance data at several detail levels, finding slow operations and call paths, examining memory use, and choosing follow-up optimizations.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ascend-ai-coding/awesome-ascend-skills/ai4s-profiling
Install

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.

Any agent
npx skills add ascend-ai-coding/awesome-ascend-skills --skill ai4s-profiling
Clone the repo
git clone --depth 1 https://github.com/ascend-ai-coding/awesome-ascend-skills

Made for: Claude Code.

Or install ascend-ai-for-science, the plugin that ships this one along with the rest of its 14 skills.

Wrote 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.

agentmods badge for ai-for-science-ai4s-profiling

README.md
[![agentmods](https://agentmods.dev/badge/skills/ascend-ai-coding/awesome-ascend-skills/ai4s-profiling/github.svg)](https://agentmods.dev/skills/ascend-ai-coding/awesome-ascend-skills/ai4s-profiling)
Your own site
<a href="https://agentmods.dev/skills/ascend-ai-coding/awesome-ascend-skills/ai4s-profiling"><img src="https://agentmods.dev/badge/skills/ascend-ai-coding/awesome-ascend-skills/ai4s-profiling/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.

agentmods 80×15 button for ai-for-science-ai4s-profiling

Your own site · 80×15
<a href="https://agentmods.dev/skills/ascend-ai-coding/awesome-ascend-skills/ai4s-profiling"><img src="https://agentmods.dev/badge/skills/ascend-ai-coding/awesome-ascend-skills/ai4s-profiling.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 93 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,134 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00093 $0.04134
Opus 5 $0.00046 $0.02067
Sonnet 5 $0.00019 $0.00827
Haiku 4.5 $0.00009 $0.00413

Measured 6d ago against content hash 15a7ea544386, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

ai-for-science-ai4s-profiling 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 6d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/validate_profiling_env.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/ai-for-science/ai4s-profiling/SKILL.md · 483 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

  1. 6d ago First seen · 483 lines · 93 tokens per session scan A 15a7ea544386

Subscribe to this mod's changes

ai-for-science-ai4s-profiling is a skill published in the GitHub repository ascend-ai-coding/awesome-ascend-skills (167 stars, last pushed yesterday), with no licence file. It adds 93 tokens to every session and 4,134 once invoked, about $0.0005 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 2026-09-05.

Related

Other skills, from other repositories

ascend-transformer-boost

An index of skills for developing with Huawei’s Ascend Transformer Boost (ATB) library. It groups eight skills covering CANN setup, ATB testing, operator replacement design, and migration to ACLNN for Ascend NPU development.

Ascend/agent-skills · 90 tokens

cann-nnal-installer

An installation guide for Huawei Ascend CANN, a software toolkit for running applications on Ascend neural-processing hardware. It covers the CANN Toolkit, kernels, and NNAL components.

Ascend/agent-skills · 80 tokens

atb-nnal-installer

An installation guide for the Ascend NPU NNAL acceleration library. It handles installing the NNAL package, setting its environment variables, and checking that it works.

Ascend/agent-skills · 55 tokens

performance-analysis

Comprehensive performance analysis, bottleneck detection, and optimization recommendations for Claude Flow swarms.

ruvnet/ruflo · 20 tokens

evaluating-cosmos-policy

Evaluates NVIDIA Cosmos Policy on LIBERO and RoboCasa simulation environments. Use when setting up cosmos-policy for robot manipulation evaluation, running headless GPU evaluations with EGL rendering, or profiling inference latency on cluster or local GPU machines.

Orchestra-Research/AI-Research-SKILLs · 51 tokens

profiling

Diagnose frame-rate bottlenecks (CPU vs GPU bound FIRST), control Unreal Insights traces, sample live frame times, and annotate performance captures. Use when FPS is low/bad, the game is slow, or you need to find what is limiting the frame rate.

kevinpbuckley/VibeUE · 57 tokens