Cutlass Skill
slowlyC/agent-gpu-skills
Write, debug, and optimize CUTLASS, CuTe, and CuTeDSL GPU kernels from local upstream source, examples, and headers.
Scaffold a new CV-CUDA operator — a complete, wired, building skeleton — and delegate the implementation to a human or another AI.
Install Make Op Scaffold
$ npx skills add CVCUDA/CV-CUDA --skill make-op-scaffold -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install CVCUDA/CV-CUDA make-op-scaffold --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/CVCUDA/CV-CUDA.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/make-op-scaffold .claude/skills/make-op-scaffold && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "make-op-scaffold" agent skill from https://github.com/CVCUDA/CV-CUDA/tree/main/.agents/skills/make-op-scaffold into .claude/skills/make-op-scaffold/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "make-op-scaffold", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/CVCUDA/CV-CUDA/tree/main/.agents/skills/make-op-scaffoldType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add CVCUDA/CV-CUDA --skill make-op-scaffold -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install CVCUDA/CV-CUDA make-op-scaffold --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/CVCUDA/CV-CUDA.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/make-op-scaffold .agents/skills/make-op-scaffold && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "make-op-scaffold" agent skill from https://github.com/CVCUDA/CV-CUDA/tree/main/.agents/skills/make-op-scaffold into .agents/skills/make-op-scaffold/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "make-op-scaffold", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add CVCUDA/CV-CUDA --skill make-op-scaffold -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install CVCUDA/CV-CUDA make-op-scaffold --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/CVCUDA/CV-CUDA.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/make-op-scaffold .cursor/skills/make-op-scaffold && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "make-op-scaffold" agent skill from https://github.com/CVCUDA/CV-CUDA/tree/main/.agents/skills/make-op-scaffold into .cursor/skills/make-op-scaffold/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "make-op-scaffold", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/CVCUDA/CV-CUDA.git --path .agents/skills/make-op-scaffold--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add CVCUDA/CV-CUDA --skill make-op-scaffold -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install CVCUDA/CV-CUDA make-op-scaffold --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/CVCUDA/CV-CUDA.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/make-op-scaffold .gemini/skills/make-op-scaffold && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "make-op-scaffold" agent skill from https://github.com/CVCUDA/CV-CUDA/tree/main/.agents/skills/make-op-scaffold into .gemini/skills/make-op-scaffold/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "make-op-scaffold", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install CVCUDA/CV-CUDA make-op-scaffoldInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add CVCUDA/CV-CUDA --skill make-op-scaffold -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/CVCUDA/CV-CUDA.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/make-op-scaffold .github/skills/make-op-scaffold && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "make-op-scaffold" agent skill from https://github.com/CVCUDA/CV-CUDA/tree/main/.agents/skills/make-op-scaffold into .github/skills/make-op-scaffold/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "make-op-scaffold", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add CVCUDA/CV-CUDA --skill make-op-scaffold -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install CVCUDA/CV-CUDA make-op-scaffold --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/CVCUDA/CV-CUDA.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/make-op-scaffold .opencode/skills/make-op-scaffold && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "make-op-scaffold" agent skill from https://github.com/CVCUDA/CV-CUDA/tree/main/.agents/skills/make-op-scaffold into .opencode/skills/make-op-scaffold/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "make-op-scaffold", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
make-op-scaffold- GitHub stars
- 2.7k
- Token cost
- ~306 tokens
- SKILL.md length
- 103 words
- Files
- 1
- Skills in repo
- 12
- Repo updated
- First seen
- Licence
- Custom licence
At a glance
Scaffold a new CV-CUDA operator — a complete, wired, building skeleton — and delegate the implementation to a human or another AI.
- Asked to set up / stub out a new operator without implementing it
- Calls python3
- Bootstrap one for someone else to finish
What it does
Make Op Scaffold is an agent skill from CVCUDA/CV-CUDA. Scaffold a new CV-CUDA operator — a complete, wired, building skeleton — and delegate the implementation to a human or another AI. Use when asked to set up / stub out a new operator without implementing it, or to bootstrap one for someone else to finish. Supports --bare (skip the spec when the definition itself is delegated).
Its SKILL.md is about 310 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in AI & LLM Engineering. It works with CUDA, NVIDIA AI Platform and Python. The repository describes itself as: CV-CUDA™ is an open-source, GPU accelerated library for cloud-scale image processing and computer vision.
When your agent uses it
- Asked to set up / stub out a new operator without implementing it
- Bootstrap one for someone else to finish
Example prompts
- “/make-op-scaffold”
Requirements
- Python 3
What it can do on your machine
Read from SKILL.md and the folder at commit b051f32. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
python3
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Make Op Scaffold loads about 306 tokens when it runs. Until then it costs about 86 tokens; SKILL.md has 103 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 103 words (~306 tokens).
“[//]: # "SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved." [//]: # "SPDX-License-Identifier: Apache-2.0"”
- name
- make-op-scaffold
Files
Just SKILL.md in .agents/skills/make-op-scaffold of CVCUDA/CV-CUDA.
Open the folder on GitHubat commit b051f32
Compare with similar skills
Make Op Scaffold next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Make Op Scaffold this skillCVCUDA/CV-CUDA | 2.7k | — | ~306 | Automated safety check: Pass | Custom licence | |
| Cutlass SkillslowlyC/agent-gpu-skills | 169 | — | ~1.3k | Automated safety check: Pass | MIT | |
| Triton SkillslowlyC/agent-gpu-skills | 169 | — | ~1.3k | Automated safety check: Pass | MIT | |
| Vllm Deploy Simplevllm-project/vllm-skills | 103 | — | ~1.6k | Automated safety check: Pass | Apache-2.0 | |
| Hyperpod Version Checkerawslabs/agent-plugins | 915 | 1 repos | ~910 | Automated safety check: Pass | Apache-2.0 | |
| Quark Env Preflightamd/Quark | 181 | — | ~1.4k | Automated safety check: Pass | MIT |
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More from CVCUDA/CV-CUDA
All 12 skills in this repoRefactor Op
CVCUDA/CV-CUDA
Find and safely apply per-operator refactoring / redundancy-reduction opportunities in a CV-CUDA operator (near-duplicate Tensor/VarShape kernels, reinvented shared utilities, dead code).
Optimize Op
CVCUDA/CV-CUDA
Drive a single-operator optimization campaign per .agents/guidance/OPTIMIZATIONGUIDELINES.md, with a deterministically enforced definition-of-done and versioned MR summary.
Review Op
CVCUDA/CV-CUDA
Review a CV-CUDA operator end-to-end (support / test / bench / docs coverage).
Optimize Op Verify
CVCUDA/CV-CUDA
Verify a CV-CUDA optimization campaign's deterministic definition-of-done and concise versioned MR summary per .agents/guidance/OPTIMIZATIONGUIDELINES.md.
Make Op
CVCUDA/CV-CUDA
Add a new CV-CUDA operator end-to-end per .agents/guidance/MAKEOPGUIDELINES.md, with a deterministically-enforced definition-of-done.
Make Op Verify
CVCUDA/CV-CUDA
Verify a new CV-CUDA operator against the deterministic final regression checklist (the /make-op done-gate).
Related
Works with
Categories
Questions about Make Op Scaffold
What does Make Op Scaffold do?
Scaffold a new CV-CUDA operator — a complete, wired, building skeleton — and delegate the implementation to a human or another AI. Make Op Scaffold is an agent skill from CVCUDA/CV-CUDA. Scaffold a new CV-CUDA operator — a complete, wired, building skeleton — and delegate the implementation to a human or another AI.
When should I use Make Op Scaffold?
Make Op Scaffold fits situations like: asked to set up / stub out a new operator without implementing it; bootstrap one for someone else to finish.
How do I install Make Op Scaffold in Claude Code?
Run `npx skills add CVCUDA/CV-CUDA --skill make-op-scaffold -a claude-code`. Or copy the skill folder (.agents/skills/make-op-scaffold in CVCUDA/CV-CUDA) into .claude/skills/make-op-scaffold in your project. Claude Code loads it when a task matches its description.
How do I install Make Op Scaffold in Codex?
Run `npx skills add CVCUDA/CV-CUDA --skill make-op-scaffold -a codex`. Or copy the skill folder (.agents/skills/make-op-scaffold in CVCUDA/CV-CUDA) into .agents/skills/make-op-scaffold in your project. Codex loads it when a task matches its description.
Can I use Make Op Scaffold in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add CVCUDA/CV-CUDA --skill make-op-scaffold -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/make-op-scaffold, .gemini/skills/make-op-scaffold, .github/skills/make-op-scaffold and .opencode/skills/make-op-scaffold in your project.
What does Make Op Scaffold need to run?
Going by SKILL.md and its folder, Make Op Scaffold needs the command-line tools its instructions call (python3). Our summary lists: Python 3.
Does Make Op Scaffold access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Make Op Scaffold safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Make Op Scaffold use?
Make Op Scaffold has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.
How many tokens does Make Op Scaffold use?
About 306 tokens (SKILL.md is roughly 1.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Make Op Scaffold?
Skills that share tags, products or a category with Make Op Scaffold: Cutlass Skill (slowlyC/agent-gpu-skills, 169 stars), Triton Skill (slowlyC/agent-gpu-skills, 169 stars), Vllm Deploy Simple (vllm-project/vllm-skills, 103 stars) and Hyperpod Version Checker (awslabs/agent-plugins, 915 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Make Op Scaffold?
CVCUDA (a GitHub organization) maintains it in CVCUDA/CV-CUDA, which has 2,728 GitHub stars. The repository holds 12 skills in this directory. The repository was last updated on September 16, 2026.
Source: CVCUDA/CV-CUDA on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.