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TensorRT-LLM: Skill for Claude Code

.claude/skills/perf-workload-profiling/SKILL.md

perf-workload-profiling is a skill for Claude Code from NVIDIA/TensorRT-LLM. It costs 187 tokens per session (1,886 once invoked), scanned A, original, no licence file.

A code-instrumentation guide for measuring how long workloads take. It covers training loops and individual GPU operations, including warmup runs, repeated measurements, and timing statistics.

In plain words
What is it for?
Use it to measure training-iteration latency, data-loading time, throughput, or CUDA kernel and operation timing.
Why use it?
It helps reveal where time is spent and avoids misleading performance measurements.

Skill for Claude Code ✓ vendor

Written for Claude Code: installed under .claude/.

This is NVIDIA/TensorRT-LLM's own configuration. It tells Claude Code how to work on TensorRT-LLM itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything TensorRT-LLM configures →

not rated 15krepo +41 today A scan SkillSpector: pass 187 tokens custom licence
View source ↗ NVIDIA/TensorRT-LLM nvidia.github.io
Reuse

Borrowing it

Nothing to install: this file belongs to NVIDIA/TensorRT-LLM. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/NVIDIA/TensorRT-LLM/main/.claude/skills/perf-workload-profiling/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/NVIDIA/TensorRT-LLM

Made for: Claude Code.

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 perf-workload-profiling

README.md
[![agentmods](https://agentmods.dev/badge/skills/nvidia/tensorrt-llm/perf-workload-profiling/github.svg)](https://agentmods.dev/skills/nvidia/tensorrt-llm/perf-workload-profiling)
Your own site
<a href="https://agentmods.dev/skills/nvidia/tensorrt-llm/perf-workload-profiling"><img src="https://agentmods.dev/badge/skills/nvidia/tensorrt-llm/perf-workload-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 perf-workload-profiling

Your own site · 80×15
<a href="https://agentmods.dev/skills/nvidia/tensorrt-llm/perf-workload-profiling"><img src="https://agentmods.dev/badge/skills/nvidia/tensorrt-llm/perf-workload-profiling.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 187 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,886 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00187 $0.01886
Opus 5.5 $0.00075 $0.00754
Sonnet 5.5 $0.00037 $0.00377
Haiku 4.5 $0.00019 $0.00189

Measured 2mo ago against content hash f68a26436acc, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

perf-workload-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 2mo 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.

.claude/skills/perf-workload-profiling/SKILL.md · 200 lines

The source is not reproduced here

A licence we could not identify

The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.

Read it on GitHub

Files

What ships with it

3 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. 2mo ago First seen · 200 lines · 187 tokens per session scan A f68a26436acc

Subscribe to this mod's changes

perf-workload-profiling is a skill published in the GitHub repository NVIDIA/TensorRT-LLM (15,021 stars, last pushed today), with no licence file. It adds 187 tokens to every session and 1,886 once invoked, about $0.0007 per session on Opus 5.5. 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.

Analytics and metricsPyTorchblackwellcudallm-servingmoe
Related

perf-workload-profiling compared with skills from other repositories

perf-workload-profiling next to 6 skills from other repositories
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perf-workload-profilingNVIDIA/TensorRT-LLMSkill15ktodaynoneA187Claude Code
sglang-diffusion-performancesgl-project/sglangSkill39ktodayApache-2.0A29Claude Code, Codex
sglang-diffusion-add-modelsgl-project/sglangSkill39ktodayApache-2.0A24Claude Code, Codex
sglang-diffusion-cache-ditsgl-project/sglangSkill39ktodayApache-2.0A161Claude Code
sglang-diffusion-modelopt-quantsgl-project/sglangSkill39ktodayApache-2.0A49Claude Code, Codex
sglang-diffusion-benchmark-profilesgl-project/sglangSkill39ktodayApache-2.0A26Claude Code, Codex
next_cutedsl_megamoeflashinfer-ai/flashinferSkill6.9ktodayApache-2.0A0Claude Code, Codex