Official agent skill

Create Cuda Python Pull Request

Create a CUDA Python pull request from an approved personal or organization-owned fork, including the GitHub CLI GraphQL fallback for renamed organization-owned forks.

OfficialApache-2.0Auto-check passedDevelopment

Install Create Cuda Python Pull Request

skills CLI

$ npx skills add NVIDIA/cuda-python --skill create-cuda-python-pull-request -a claude-code

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

GitHub CLI

$ gh skill install NVIDIA/cuda-python create-cuda-python-pull-request --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/NVIDIA/cuda-python.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/create-cuda-python-pull-request .claude/skills/create-cuda-python-pull-request && 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/

Paste into Claude Code

Install the "create-cuda-python-pull-request" agent skill from https://github.com/NVIDIA/cuda-python/tree/main/.agents/skills/create-cuda-python-pull-request into .claude/skills/create-cuda-python-pull-request/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "create-cuda-python-pull-request", 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

$skill-installer install https://github.com/NVIDIA/cuda-python/tree/main/.agents/skills/create-cuda-python-pull-request

Type 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.

skills CLI

$ npx skills add NVIDIA/cuda-python --skill create-cuda-python-pull-request -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install NVIDIA/cuda-python create-cuda-python-pull-request --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/NVIDIA/cuda-python.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/create-cuda-python-pull-request .agents/skills/create-cuda-python-pull-request && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "create-cuda-python-pull-request" agent skill from https://github.com/NVIDIA/cuda-python/tree/main/.agents/skills/create-cuda-python-pull-request into .agents/skills/create-cuda-python-pull-request/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "create-cuda-python-pull-request", 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.

skills CLI

$ npx skills add NVIDIA/cuda-python --skill create-cuda-python-pull-request -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install NVIDIA/cuda-python create-cuda-python-pull-request --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/NVIDIA/cuda-python.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/create-cuda-python-pull-request .cursor/skills/create-cuda-python-pull-request && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "create-cuda-python-pull-request" agent skill from https://github.com/NVIDIA/cuda-python/tree/main/.agents/skills/create-cuda-python-pull-request into .cursor/skills/create-cuda-python-pull-request/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "create-cuda-python-pull-request", 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

$ gemini skills install https://github.com/NVIDIA/cuda-python.git --path .agents/skills/create-cuda-python-pull-request

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add NVIDIA/cuda-python --skill create-cuda-python-pull-request -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install NVIDIA/cuda-python create-cuda-python-pull-request --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/NVIDIA/cuda-python.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/create-cuda-python-pull-request .gemini/skills/create-cuda-python-pull-request && rm -rf skills-src

Use ~/.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/

Paste into Gemini CLI

Install the "create-cuda-python-pull-request" agent skill from https://github.com/NVIDIA/cuda-python/tree/main/.agents/skills/create-cuda-python-pull-request into .gemini/skills/create-cuda-python-pull-request/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "create-cuda-python-pull-request", 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.

GitHub CLI

$ gh skill install NVIDIA/cuda-python create-cuda-python-pull-request

Installs 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).

skills CLI

$ npx skills add NVIDIA/cuda-python --skill create-cuda-python-pull-request -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/NVIDIA/cuda-python.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/create-cuda-python-pull-request .github/skills/create-cuda-python-pull-request && rm -rf skills-src

Use ~/.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/

Paste into GitHub Copilot

Install the "create-cuda-python-pull-request" agent skill from https://github.com/NVIDIA/cuda-python/tree/main/.agents/skills/create-cuda-python-pull-request into .github/skills/create-cuda-python-pull-request/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "create-cuda-python-pull-request", 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.

skills CLI

$ npx skills add NVIDIA/cuda-python --skill create-cuda-python-pull-request -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install NVIDIA/cuda-python create-cuda-python-pull-request --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/NVIDIA/cuda-python.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/create-cuda-python-pull-request .opencode/skills/create-cuda-python-pull-request && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "create-cuda-python-pull-request" agent skill from https://github.com/NVIDIA/cuda-python/tree/main/.agents/skills/create-cuda-python-pull-request into .opencode/skills/create-cuda-python-pull-request/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "create-cuda-python-pull-request", 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: create-cuda-python-pull-request
GitHub stars: 3.4k
Token cost: ~1.1k tokens
SKILL.md length: 379 words
Files: 2
Skills in repo: 1
Repo updated: Oct 7, 2026
First seen: Oct 7, 2026
Licence: Apache-2.0

At a glance

Create a CUDA Python pull request from an approved personal or organization-owned fork, including the GitHub CLI GraphQL fallback for renamed organization-owned forks.

Works in 5 steps: Run git status --short --branch, inspect… → Run git remote -v and resolve the… → Confirm through GitHub that the push… → …
The user directly requests creating
SKILL.md covers Inspect the topology and…, Validate and push, Create the pull request and Handle renamed…
Calls gh and git

What it does

Create Cuda Python Pull Request is an agent skill from NVIDIA/cuda-python, published by the product's own GitHub organization. Create a CUDA Python pull request from an approved personal or organization-owned fork, including the GitHub CLI GraphQL fallback for renamed organization-owned forks. Use when the user directly requests creating or opening a CUDA Python pull request. Do not use for local implementation, commits, pushes, branch preparation, PR advice, or general GitHub work without that direct request.

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `agents/openai.yaml`).

It sits in Development, covering Pull requests and GraphQL. It works with CUDA, Python, GitHub and GraphQL. The repository describes itself as: CUDA Python: Performance meets Productivity. The licence is Apache-2.0.

When your agent uses it

The user directly requests creating
Opening a CUDA Python pull request
Local implementation
Branch preparation

Example prompts

“/create-cuda-python-pull-request”

Requirements

Python 3

Workflow steps

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

Run git status --short --branch, inspect the branch diff, and confirm the
Run git remote -v and resolve the complete OWNER/REPOSITORY names of the
Confirm through GitHub that the push target is a fork of the base repository
Confirm that the intended push target complies with the repository's
Inspect the repository's pull-request template, available labels, and open

What it can do on your machine

Read from SKILL.md and the folder at commit 5078fe6. 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:
- gh
- git
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
- github.com
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

Create Cuda Python Pull Request loads about 1.1k tokens when it runs. Until then it costs about 105 tokens; SKILL.md has 379 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~105
When it runs · the whole SKILL.md, loaded when a task matches: ~1.1k

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

The full file from NVIDIA/cuda-python at commit 5078fe6, republished under its Apache-2.0 licence (© NVIDIA). 379 words, ~1,128 tokens.

Download SKILL.mdSave it as .claude/skills/create-cuda-python-pull-request/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.

name: create-cuda-python-pull-request
description: Create a CUDA Python pull request from an approved personal or organization-owned fork, including the GitHub CLI GraphQL fallback for renamed organization-owned forks. Use when the user directly requests creating or opening a CUDA Python pull request. Do not use for local implementation, commits, pushes, branch preparation, PR advice, or general GitHub work without that direct request.

Create CUDA Python Pull Request

This skill supplies technical procedure after the user directly asks to create a pull request. It does not define when a pull request should be created or authorize one without that direct request. Do not infer the request from completed work, a local commit, a push request, or the existence of a suitable fork.

Inspect the topology and proposed change

Run git status --short --branch, inspect the branch diff, and confirm the intended base branch.
Run git remote -v and resolve the complete OWNER/REPOSITORY names of the base repository and intended fork. Do not rely on remote names alone.
Confirm through GitHub that the push target is a fork of the base repository and is not the base repository itself.
Confirm that the intended push target complies with the repository's remote-write policy and the user's request.
Inspect the repository's pull-request template, available labels, and open milestones. Do not guess required metadata; ask the user when it is unclear.

Validate and push

Run the checks appropriate to the change and review the final diff. Push the current branch to the approved fork using the explicit remote and branch:

bash

git push <fork-remote> <branch>

Show full SKILL.md (182 more words)Show less

Create the pull request

Prepare a complete body from the repository's pull-request template. Every pull request must have at least one assignee, one label, and a milestone; CI enforces this through pr-metadata-check.

Use gh pr create when it can identify the fork unambiguously. Select the base repository and branch explicitly and supply the required metadata:

bash

gh pr create \
  --repo <base-owner>/<base-repository> \
  --base <base-branch> \
  --head <fork-owner>:<head-branch> \
  --title "<title>" \
  --body-file <path-to-pr-body> \
  --assignee <assignee> \
  --label <label> \
  --milestone <milestone>

Add --draft when the user requests a draft pull request.

Handle renamed organization-owned forks

GitHub CLI issue cli/cli#10093 tracks gh pr create support for cross-repository pull requests within one organization. Check whether the issue has been resolved before using the workaround.

If gh pr create cannot identify an organization-owned fork whose repository name differs from the base repository, create the pull request with GitHub's GraphQL API and pass headRepositoryId explicitly.

Resolve the repository node IDs:

bash

BASE_REPO="<base-owner>/<base-repository>"
HEAD_REPO="<fork-owner>/<fork-repository>"
BASE_REPO_ID="$(gh api "repos/${BASE_REPO}" --jq '.node_id')"
HEAD_REPO_ID="$(gh api "repos/${HEAD_REPO}" --jq '.node_id')"

Create the pull request. Set draft to match the user's request.

bash

gh api graphql \
  -f repositoryId="${BASE_REPO_ID}" \
  -f headRepositoryId="${HEAD_REPO_ID}" \
  -f baseRefName="<base-branch>" \
  -f headRefName="<head-branch>" \
  -f title="<title>" \
  -F body="@<path-to-pr-body>" \
  -F draft=false \
  -f query='
    mutation CreatePullRequest(
      $repositoryId: ID!
      $headRepositoryId: ID!
      $baseRefName: String!
      $headRefName: String!
      $title: String!
      $body: String!
      $draft: Boolean!
    ) {
      createPullRequest(input: {
        repositoryId: $repositoryId
        headRepositoryId: $headRepositoryId
        baseRefName: $baseRefName
        headRefName: $headRefName
        title: $title
        body: $body
        draft: $draft
      }) {
        pullRequest { number url }
      }
    }' \
  --jq '.data.createPullRequest.pullRequest'

The GraphQL API does not populate the pull-request template automatically. After creation, add the required metadata to the returned pull-request number:

bash

gh pr edit <pr-number> \
  --repo "${BASE_REPO}" \
  --add-assignee "<assignee>" \
  --add-label "<label>" \
  --milestone "<milestone>"

Verify the resulting URL, base branch, head repository and branch, draft state, body, assignee, label, and milestone before reporting completion.

Files

SKILL.md and 1 other file in .agents/skills/create-cuda-python-pull-request of NVIDIA/cuda-python.

SKILL.md
agents/openai.yaml

Open the folder on GitHubat commit 5078fe6

Compare with similar skills

Create Cuda Python Pull Request 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.

Create Cuda Python Pull Request compared with similar skills
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Create Cuda Python Pull Request this skillNVIDIA/cuda-python	3.4k	—	~1.1k	Automated safety check: Pass	Apache-2.0	today
Gh QueueLanternOps/breeze	130	—	~5k	Automated safety check: Pass	AGPL-3.0	today
Review PR Commentslatitude-dev/latitude-llm	4.7k	—	~2.6k	Automated safety check: Pass	MIT	yesterday
GitHub Opsdaymade/claude-code-skills	1.4k	—	~3.7k	Automated safety check: Pass	MIT	today
Backend AI Guidelablup/backend.ai-webui	133	1 repos	~1.8k	Automated safety check: Pass	LGPL-3.0	today
Reply To PR Threadstobihagemann/turbo	406	—	~941	Automated safety check: Pass	MIT	yesterday

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Works with

Questions about Create Cuda Python Pull Request

What does Create Cuda Python Pull Request do?

Create a CUDA Python pull request from an approved personal or organization-owned fork, including the GitHub CLI GraphQL fallback for renamed organization-owned forks. Create Cuda Python Pull Request is an agent skill from NVIDIA/cuda-python, published by the product's own GitHub organization. Create a CUDA Python pull request from an approved personal or organization-owned fork, including the GitHub CLI GraphQL fallback for renamed organization-owned forks.

When should I use Create Cuda Python Pull Request?

Create Cuda Python Pull Request fits situations like: the user directly requests creating; opening a CUDA Python pull request; local implementation; branch preparation.

How do I install Create Cuda Python Pull Request in Claude Code?

Run `npx skills add NVIDIA/cuda-python --skill create-cuda-python-pull-request -a claude-code`. Or copy the skill folder (.agents/skills/create-cuda-python-pull-request in NVIDIA/cuda-python) into .claude/skills/create-cuda-python-pull-request in your project. Claude Code loads it when a task matches its description.

How do I install Create Cuda Python Pull Request in Codex?

Run `npx skills add NVIDIA/cuda-python --skill create-cuda-python-pull-request -a codex`. Or copy the skill folder (.agents/skills/create-cuda-python-pull-request in NVIDIA/cuda-python) into .agents/skills/create-cuda-python-pull-request in your project. Codex loads it when a task matches its description.

Can I use Create Cuda Python Pull Request 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 NVIDIA/cuda-python --skill create-cuda-python-pull-request -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/create-cuda-python-pull-request, .gemini/skills/create-cuda-python-pull-request, .github/skills/create-cuda-python-pull-request and .opencode/skills/create-cuda-python-pull-request in your project.

What does Create Cuda Python Pull Request need to run?

Going by SKILL.md and its folder, Create Cuda Python Pull Request needs the command-line tools its instructions call (gh and git). Our summary lists: Python 3.

Does Create Cuda Python Pull Request access the network?

SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.

Is Create Cuda Python Pull Request 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 Create Cuda Python Pull Request use?

Create Cuda Python Pull Request is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Create Cuda Python Pull Request use?

About 1.1k tokens (SKILL.md is roughly 4.5k 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 Create Cuda Python Pull Request?

Skills that share tags, products or a category with Create Cuda Python Pull Request: Gh Queue (LanternOps/breeze, 130 stars), Review PR Comments (latitude-dev/latitude-llm, 4.7k stars), GitHub Ops (daymade/claude-code-skills, 1.4k stars) and Backend AI Guide (lablup/backend.ai-webui, 133 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Create Cuda Python Pull Request?

NVIDIA (a GitHub organization, an official publisher) maintains it in NVIDIA/cuda-python, which has 3,394 GitHub stars. The repository was last updated on October 7, 2026.

Source: NVIDIA/cuda-python on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Create Cuda Python Pull Request

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Create CUDA Python Pull Request

Inspect the topology and proposed change

Validate and push

Create the pull request

Handle renamed organization-owned forks

Files

Compare with similar skills

Similar skills

Gh Queue

Review PR Comments

GitHub Ops

Backend AI Guide

Reply To PR Threads

GitHub Fork and PR Submission

Related

Questions about Create Cuda Python Pull Request