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Agent skill

Make Op

by CVCUDA in CVCUDA/CV-CUDA

Add a new CV-CUDA operator end-to-end per .agents/guidance/MAKEOPGUIDELINES.md, with a deterministically-enforced definition-of-done.

Custom licenceAuto-check passedTesting & QA

Install Make Op

skills CLI
$ npx skills add CVCUDA/CV-CUDA --skill make-op -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install CVCUDA/CV-CUDA make-op --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ 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 .claude/skills/make-op && rm -rf skills-src

Use ~/.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/

Facts

Skill name
make-op
GitHub stars
2.7k
Token cost
~831 tokens
SKILL.md length
340 words
Files
1
Skills in repo
12
Repo updated
First seen
Licence
Custom licence

At a glance

Add a new CV-CUDA operator end-to-end per .agents/guidance/MAKEOPGUIDELINES.md, with a deterministically-enforced definition-of-done.

  • Works in 6 steps: Spec & approval (Part 0) — propose the… → Scaffold — tools/mkop/mkop.sh → the… → Implement — kernel + an independent CPU… → …
  • Asked to create/add a new operator
  • Calls python3
  • Verify that a new operator is complete (approved spec

What it does

Make Op is an agent skill from CVCUDA/CV-CUDA. Add a new CV-CUDA operator end-to-end per .agents/guidance/MAKEOPGUIDELINES.md, with a deterministically-enforced definition-of-done. Use when asked to create/add a new operator, scaffold one, or verify that a new operator is complete (approved spec, wired scaffold, bit-exact regression tests across the declared support matrix, required layout parity, complement negatives, docs + relnote, benched dtypes, tests that run and pass, optimization-ready).

Its SKILL.md is about 830 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 Testing & QA. It works with CUDA, Python and NVIDIA AI Platform. 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 create/add a new operator
  • Verify that a new operator is complete (approved spec
  • Bit-exact regression tests across the declared support matrix
  • Required layout parity

Example prompts

  • “/make-op”

Requirements

  • Python 3

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Spec & approval (Part 0) — propose the operator's semantics + a cited reference oracle
  2. Scaffold — tools/mkop/mkop.sh → the wired skeleton; gate with
  3. Implement — kernel + an independent CPU gold reference + tests/bench per the COV-* rules
  4. Done gate — python3 tools/make_op.py --phase done --run: composes /review-op
  5. Calibrate + seed baselines — calibrate each bench config to 1–2 ms nvbench GPU time
  6. Hand off to /optimize-op for the performance campaign.

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 loads about 831 tokens when it runs. Until then it costs about 116 tokens; SKILL.md has 340 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~116
When it runs · the whole SKILL.md, loaded when a task matches
~831

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 340 words (~831 tokens).

“[//]: # "SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved." [//]: # "SPDX-License-Identifier: Apache-2.0"”

— opening of SKILL.md by CVCUDA, Custom licence
name
make-op

Read the full SKILL.md on GitHub

Files

Just SKILL.md in .agents/skills/make-op of CVCUDA/CV-CUDA.

Open the folder on GitHubat commit b051f32

Compare with similar skills

Make Op 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.

Make Op compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Make Op this skillCVCUDA/CV-CUDA2.7k—~831Automated safety check: PassCustom licence
Jetson Video SetupNVIDIA/skills3.5k1 repos~2.4kAutomated safety check: NotesApache-2.0
Cutlass SkillslowlyC/agent-gpu-skills169—~1.3kAutomated safety check: PassMIT
Triton SkillslowlyC/agent-gpu-skills169—~1.3kAutomated safety check: PassMIT
Vllm Deploy Simplevllm-project/vllm-skills103—~1.6kAutomated safety check: PassApache-2.0
Hyperpod Version Checkerawslabs/agent-plugins9121 repos~910Automated safety check: PassApache-2.0

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More from CVCUDA/CV-CUDA

All 12 skills in this repo

  • Refactor 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).

    2.7k GitHub stars~1.5k tokensUpdated 21 days ago
    Auto-check passed

  • 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.

    2.7k GitHub stars~834 tokensUpdated 21 days ago
    Auto-check passed

  • Review Op

    CVCUDA/CV-CUDA

    Review a CV-CUDA operator end-to-end (support / test / bench / docs coverage).

    2.7k GitHub stars~481 tokensUpdated 21 days ago
    Auto-check passed

  • 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.

    2.7k GitHub stars~424 tokensUpdated 21 days ago
    Auto-check passed

  • Make Op Scaffold

    CVCUDA/CV-CUDA

    Scaffold a new CV-CUDA operator — a complete, wired, building skeleton — and delegate the implementation to a human or another AI.

    2.7k GitHub stars~306 tokensUpdated 21 days ago
    Auto-check passed

  • Make Op Verify

    CVCUDA/CV-CUDA

    Verify a new CV-CUDA operator against the deterministic final regression checklist (the /make-op done-gate).

    2.7k GitHub stars~433 tokensUpdated 21 days ago
    Auto-check passed

Works with

Categories

Questions about Make Op

What does Make Op do?

Add a new CV-CUDA operator end-to-end per .agents/guidance/MAKEOPGUIDELINES.md, with a deterministically-enforced definition-of-done. Make Op is an agent skill from CVCUDA/CV-CUDA.md, with a deterministically-enforced definition-of-done.

When should I use Make Op?

Make Op fits situations like: asked to create/add a new operator; verify that a new operator is complete (approved spec; bit-exact regression tests across the declared support matrix; required layout parity.

How do I install Make Op in Claude Code?

Run `npx skills add CVCUDA/CV-CUDA --skill make-op -a claude-code`. Or copy the skill folder (.agents/skills/make-op in CVCUDA/CV-CUDA) into .claude/skills/make-op in your project. Claude Code loads it when a task matches its description.

How do I install Make Op in Codex?

Run `npx skills add CVCUDA/CV-CUDA --skill make-op -a codex`. Or copy the skill folder (.agents/skills/make-op in CVCUDA/CV-CUDA) into .agents/skills/make-op in your project. Codex loads it when a task matches its description.

Can I use Make Op 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 -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, .gemini/skills/make-op, .github/skills/make-op and .opencode/skills/make-op in your project.

What does Make Op need to run?

Going by SKILL.md and its folder, Make Op needs the command-line tools its instructions call (python3). Our summary lists: Python 3.

Does Make Op 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 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 use?

Make Op 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 use?

About 831 tokens (SKILL.md is roughly 3.3k 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?

Skills that share tags, products or a category with Make Op: Jetson Video Setup (NVIDIA/skills, 3.5k stars), Cutlass Skill (slowlyC/agent-gpu-skills, 169 stars), Triton Skill (slowlyC/agent-gpu-skills, 169 stars) and Vllm Deploy Simple (vllm-project/vllm-skills, 103 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Make Op?

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.