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Agent skill

Make Op Verify

by CVCUDA in CVCUDA/CV-CUDA

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

Custom licenceAuto-check passedAI & LLM Engineering

Install Make Op Verify

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

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

GitHub CLI
$ gh skill install CVCUDA/CV-CUDA make-op-verify --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-verify .claude/skills/make-op-verify && 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-verify
GitHub stars
2.7k
Token cost
~433 tokens
SKILL.md length
153 words
Files
1
Skills in repo
12
Repo updated
First seen
Licence
Custom licence

At a glance

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

  • Asked whether a new operator is complete/done
  • Calls python3
  • Gate it before merge - gold reference
  • Bit-exact coverage across the declared support matrix

What it does

Make Op Verify is an agent skill from CVCUDA/CV-CUDA. Verify a new CV-CUDA operator against the deterministic final regression checklist (the /make-op done-gate). Use when asked whether a new operator is complete/done, or to gate it before merge - gold reference, bit-exact coverage across the declared support matrix, required layout parity, complement negatives, docs + relnote, benched dtypes, tests that run and pass, and optimization-readiness.

Its SKILL.md is about 430 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, C++ 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 whether a new operator is complete/done
  • Gate it before merge - gold reference
  • Bit-exact coverage across the declared support matrix
  • Required layout parity

Example prompts

  • “/make-op-verify”

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 Verify loads about 433 tokens when it runs. Until then it costs about 103 tokens; SKILL.md has 153 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~103
When it runs · the whole SKILL.md, loaded when a task matches
~433

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 153 words (~433 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-verify

Read the full SKILL.md on GitHub

Files

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

Open the folder on GitHubat commit b051f32

Compare with similar skills

Make Op Verify 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 Verify compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Make Op Verify this skillCVCUDA/CV-CUDA2.7k—~433Automated safety check: PassCustom licence
Cutlass SkillslowlyC/agent-gpu-skills169—~1.3kAutomated safety check: PassMIT
Cudaq GuideNVIDIA/skills3.5k—~1.3kAutomated safety check: PassApache-2.0
Cuopt DeveloperNVIDIA/skills3.5k—~3.2kAutomated safety check: NotesApache-2.0
Holoscan Install CondaNVIDIA/skills3.5k—~2kAutomated safety check: PassApache-2.0
Holoscan Install DebianNVIDIA/skills3.5k—~1.6kAutomated safety check: NotesApache-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
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  • 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
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  • 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
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  • 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

    CVCUDA/CV-CUDA

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

    2.7k GitHub stars~831 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
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Works with

Categories

Questions about Make Op Verify

What does Make Op Verify do?

Verify a new CV-CUDA operator against the deterministic final regression checklist (the /make-op done-gate). Make Op Verify is an agent skill from CVCUDA/CV-CUDA. Verify a new CV-CUDA operator against the deterministic final regression checklist (the /make-op done-gate).

When should I use Make Op Verify?

Make Op Verify fits situations like: asked whether a new operator is complete/done; gate it before merge - gold reference; bit-exact coverage across the declared support matrix; required layout parity.

How do I install Make Op Verify in Claude Code?

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

How do I install Make Op Verify in Codex?

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

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

What does Make Op Verify need to run?

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

Does Make Op Verify 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 Verify 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 Verify use?

Make Op Verify 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 Verify use?

About 433 tokens (SKILL.md is roughly 1.7k 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 Verify?

Skills that share tags, products or a category with Make Op Verify: Cutlass Skill (slowlyC/agent-gpu-skills, 169 stars), Cudaq Guide (NVIDIA/skills, 3.5k stars), Cuopt Developer (NVIDIA/skills, 3.5k stars) and Holoscan Install Conda (NVIDIA/skills, 3.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Make Op Verify?

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.