CUDA Kernel & GPU Workload Optimizer Agent Skill
Optimizes, profiles, and benchmarks CUDA, CUTLASS, Triton, and deep learning GPU workloads using evidence-driven profiling and ROI analysis.
- Context cost
- 84k tokensestimated from the bundle, loaded when it triggers
- Bundle
- 40 files · 935.2 kB18 scripts among them — read before you run
- Licence
- MITthe author’s own terms
- Last change
- —no release on file
- Servers it uses
- Noneruns standalone
What it does
Use when optimizing or diagnosing GPU workload performance with CUDA, CUTLASS, Triton, PyTorch, vLLM or TensorRT-LLM; interpreting NCU, Nsys or PyTorch Profiler evidence; or preparing the workload and correctness checks for such optimization. General coding, skill maintenance and conceptual GPU questions do not require the optimization workflow.
Installed, it changes the agent in these ways.
What this skill changes about the agent has not been set out here as a list. Its SKILL.md, shown below, says it in the author’s own words.
And these are the jobs people reach for it for.
The skill itself
A skill is instructions the model reads, so you can see what you are getting: below is the start of its SKILL.md. The front matter loads with every session, the body loads when the skill triggers, and the whole file comes with the install.
Nothing in a skill executes. The client loads the text and the model follows it, so a skill can be audited the way a runbook is — by reading it.
What it costs in context
Skills are not billed by the call. They are paid for in context: every token the instructions occupy is a token your code, your diff and your conversation cannot use. Here is what this one takes and when it takes it.
84k tokens, estimated from the bundle at four bytes to the token, held for the rest of the session once it triggers. Heavy. Teams tend to install this one per project rather than globally, and load it only when the job comes up.
A server charges by the month. A skill charges once per session, in context, and then keeps charging it for as long as the session lives.
Before and after
The same question, put to the same model twice: once as it comes, and once with these instructions loaded.
No worked example has been published for this skill yet.
The procedure it runs
The procedure has not been set out here step by step. It is in the body of its SKILL.md: the start of it is shown above, and the whole file comes with the install.
These steps are written for a model to follow, not executed by a runtime. It can still be told to skip one, and it will say so when it does.
Servers it uses
None. This skill calls no MCP servers at all.
Everything it needs is in the instructions, so it works in a project with nothing connected — the model reads the file and changes how it works with what it can already reach.
Its SKILL.md does not declare which tools it asks the agent for, so what it touches is whatever the instructions themselves ask for — read them before you install it.
This SKILL.md carries no allowed-tools line, so neither is declared. A skill grants no permissions of its own — it can only ask for tools your client already has.
What it will not do
Every skill is narrow, and the useful ones say where they stop. These are the jobs this one is the wrong tool for.
What this skill is not for has not been published here. Nothing is implied by that: it is a section the author has not filled in.
What is in the bundle
40 files, 935.2 kB on disk. Mostly text — the instructions the model reads — with 18 scripts in it that your client would run only if the instructions tell it to.
- SKILL.md9.2 kB
- LICENSE1.1 kB
- NOTICE0.8 kB
- agents/openai.yaml0.7 kB
- examples/walkthrough.md4.8 kB
- references/compatibility.md2.0 kB
- references/environment_readiness.md5.0 kB
- references/ncu_metrics_guide.md3.4 kB
- references/nonstationary_serving_evidence.md2.1 kB
- references/optimizer_limits.md0.9 kB
- references/performance_iteration.md17.6 kB
- references/request_protocol.md17.3 kB
- references/research_augmentation.md5.8 kB
- references/sass_signatures.json13.9 kB
- references/serving_evidence_protocol.md3.5 kB
- references/systems_and_ir_coverage.md2.2 kB
- references/version_stack_audit.md1.3 kB
- scripts/_invocation_runtime.py72.7 kB
- scripts/artifact_store.py58.6 kB
- scripts/champion.py17.3 kB
- scripts/compiler_evidence.py16.7 kB
- scripts/execution_map.py10.6 kB
- scripts/experiment_design.py0.8 kB
- scripts/knowledge_query.py25.7 kB
- scripts/paired_stats.py6.6 kB
- scripts/profile_ncu.py38.0 kB
- scripts/profile_nsys.py33.4 kB
- scripts/profile_pytorch.py30.9 kB
- scripts/readiness.py29.6 kB
- scripts/sass_check.py24.7 kB
- scripts/self_check.py15.8 kB
- scripts/version_audit.py9.9 kB
- scripts/workload_adapter.py75.9 kB
- scripts/workload_evaluate.py109.8 kB
- templates/workload_driver.py22.4 kB
- templates/workload_driver_request.schema.json3.4 kB
- templates/workload_driver_result.schema.json7.3 kB
- references/knowledge/cards.json199.9 kB
- references/knowledge/sources.json30.9 kB
- references/knowledge/playbooks/triton-decode-attention-gqa.md2.7 kB
A skill installs nothing and depends on nothing: it is a folder your client reads. This one carries 18 scripts beside the text, so the bundle is 40 files you can review in full before installing. The MIT licence covers the templates and examples as well as the instructions.
Install
Installing copies the bundle into your project. Nothing runs at install time — the files sit on disk until the model reads them.
# CUDA Kernel & GPU Workload Optimizer · 84k tokens when loaded · macOS, Linux
mkdir -p .claude/skills && t=$(mktemp -d) &&
curl -fsSL -o "$t/bundle.tar.gz" https://mcprush.com/api/skills/cuda-kernel-gpu-workload-optimizer/bundle.tar.gz &&
tar -xzf "$t/bundle.tar.gz" -C "$t" && [ -d "$t/cuda-kernel-gpu-workload-optimizer" ] &&
{ [ ! -e .claude/skills/cuda-kernel-gpu-workload-optimizer ] || { mv .claude/skills/cuda-kernel-gpu-workload-optimizer "$t/.previous" && echo "Previous copy moved to $t/.previous"; }; } &&
mv "$t/cuda-kernel-gpu-workload-optimizer" .claude/skills/ && echo "Installed .claude/skills/cuda-kernel-gpu-workload-optimizer"npx mcprush@latest skill add troycheng/cuda-kernel-gpu-workload-optimizerWindows PowerShell says 'running scripts is disabled on this system'? Run Set-ExecutionPolicy -Scope CurrentUser RemoteSigned once, or type npx.cmd instead of npx (codex.cmd, gemini.cmd, grok.cmd likewise). PowerShell 7 needs neither. Writes to .claude/skills/cuda-kernel-gpu-workload-optimizer/ in the current project. For every project instead, run mkdir -p ~/.claude/skills && t=$(mktemp -d) && curl -fsSL -o "$t/bundle.tar.gz" https://mcprush.com/api/skills/cuda-kernel-gpu-workload-optimizer/bundle.tar.gz && tar -xzf "$t/bundle.tar.gz" -C "$t" && [ -d "$t/cuda-kernel-gpu-workload-optimizer" ] && { [ ! -e ~/.claude/skills/cuda-kernel-gpu-workload-optimizer ] || { mv ~/.claude/skills/cuda-kernel-gpu-workload-optimizer "$t/.previous" && echo "Previous copy moved to $t/.previous"; }; } && mv "$t/cuda-kernel-gpu-workload-optimizer" ~/.claude/skills/ && echo "Installed ~/.claude/skills/cuda-kernel-gpu-workload-optimizer" (macOS, Linux) — or add --global to the npx line. The curl line replaces .claude/skills/cuda-kernel-gpu-workload-optimizer/ only after the download succeeds, so files left there by another skill of the same name, or by an older release, do not mix in. A copy already there is moved aside, not deleted, and the line prints where. It appears as cuda-kernel-optimizer in Gemini CLI, Codex, Copilot and Grok (its own name); Claude Code lists it by the folder name, cuda-kernel-gpu-workload-optimizer.
Which clients pick it up on their own
A skill is a folder of text. Most of these read a skills folder and pick it up without being told; the rest take the same folder another way — an upload in the app, a parameter on an API call — and then choose it by its description just the same.
Versions
Its author publishes no version number, so there is nothing here to pin to: what you install is the folder as it stands today. Instructions change more often than APIs do — a skill can be rewritten entirely without anything it depends on moving.
Nothing to pin to: this skill carries no version number of its own. What you install is what the folder holds on the day you install it.
Reviews
Nobody has reviewed this skill yet. The rating is the mean of the reviews written here, so there is none until somebody writes the first.
A review is tied to an account so it can be answered, edited and taken down by the person who wrote it.
Sign inAnybody with an account, one review each. It carries the version that was current when you wrote it, and the publisher may reply once.