Official agent skill

Release Branching

by intel in intel/torch-xpu-ops

A skill your agent uses when setting up a new torch-xpu-ops release branch corresponding to a PyTorch release.

OfficialApache-2.0Auto-check passedAI & LLM Engineering

Install Release Branching

skills CLI
$ npx skills add intel/torch-xpu-ops --skill release-branching -a claude-code

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

GitHub CLI
$ gh skill install intel/torch-xpu-ops release-branching --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/intel/torch-xpu-ops.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/release-branching .claude/skills/release-branching && 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
release-branching
GitHub stars
115
Token cost
~1.4k tokens
SKILL.md length
339 words
Files
1
Skills in repo
29
Repo updated
First seen
Licence
Apache-2.0

At a glance

A skill your agent uses when setting up a new torch-xpu-ops release branch corresponding to a PyTorch release.

  • Works in 5 steps: Verify PyTorch Release Branch → Create torch-xpu-ops Release Branch → Create Release Tracker Issue → …
  • Setting up a new torch-xpu-ops release branch corresponding to a PyTorch release
  • SKILL.md covers Terminology, Step 1 — Verify PyTorch…, Step 2 — Create torch-xpu-ops… and Step 3 — Create Release…, plus 3 more sections
  • Calls gh and git; reaches github.com

What it does

Release Branching is an agent skill from intel/torch-xpu-ops, published by the product's own GitHub organization. Use when setting up a new torch-xpu-ops release branch corresponding to a PyTorch release. Covers branch creation, release tracker issue, workflow default changes PR, and tracker comment.

Its SKILL.md is about 1.4k 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, covering Deep learning. It works with PyTorch. The licence is Apache-2.0.

When your agent uses it

  • Setting up a new torch-xpu-ops release branch corresponding to a PyTorch release
  • Tasks that involve Deep learning

Example prompts

  • “/release-branching”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Verify PyTorch Release Branch
  2. Create torch-xpu-ops Release Branch
  3. Create Release Tracker Issue
  4. Create Release-Only Changes PR
  5. Comment on Release Tracker Issue

What it can do on your machine

Read from SKILL.md and the folder at commit a033aa5. 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

    Hosts in commands or code, which the agent is likely to contact:

    • 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

Release Branching loads about 1.4k tokens when it runs. Until then it costs about 51 tokens; SKILL.md has 339 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~51
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k

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 intel/torch-xpu-ops at commit a033aa5, republished under its Apache-2.0 licence (© intel). 339 words, ~1,423 tokens.

Download SKILL.mdSave it as .claude/skills/release-branching/SKILL.md (or your agent's skills folder).
name
release-branching
description
Use when setting up a new torch-xpu-ops release branch corresponding to a PyTorch release. Covers branch creation, release tracker issue, workflow default changes PR, and tracker comment.

XPU Release Branching

Set up torch-xpu-ops for a new PyTorch release cycle: create the release branch, open the tracker issue, submit the workflow-defaults PR, and post the initial tracker comment.

Invocation: /xpu-release-branching release/X.Y

Terminology

Given release/2.12:

  • BRANCH = release/2.12
  • MAJOR_MINOR = 2.12
  • VERSION = v.2.12.0

Step 1 — Verify PyTorch Release Branch

Confirm the pytorch release branch exists and locate the release tracker issue:

bash
# Branch must exist
gh api repos/pytorch/pytorch/branches/release/MAJOR_MINOR --jq '.name'

# Find the pytorch release tracker issue
gh issue list -R pytorch/pytorch -s all \
  --search "[v.MAJOR_MINOR.0] Release Tracker in:title" \
  --json number,title,url -L 1

Read the pytorch release tracker issue body to extract:

  • Phase 1 deadline (e.g. "until 27/4/26")
  • Phase 2 start (e.g. "after 27/4/26")

These dates are needed for the torch-xpu-ops tracker issue.

Step 2 — Create torch-xpu-ops Release Branch

Get the pinned commit from pytorch's release branch and create the torch-xpu-ops branch from it. If the branch already exists (e.g. retrying after a partial failure), skip this step and verify the branch directly.

bash
# Get the pinned torch-xpu-ops commit on the pytorch release branch
PINNED=$(gh api repos/pytorch/pytorch/contents/third_party/xpu.txt \
  --jq '.content' -H 'Accept: application/vnd.github.v3+json' \
  -f ref=release/MAJOR_MINOR | base64 -d | tr -d '[:space:]')

# Create the release branch at that commit
gh api repos/intel/torch-xpu-ops/git/refs -f ref=refs/heads/release/MAJOR_MINOR -f sha=$PINNED

Verify the branch was created:

bash
gh api repos/intel/torch-xpu-ops/branches/release/MAJOR_MINOR --jq '.name'

Step 3 — Create Release Tracker Issue

Create a milestone PTMAJOR_MINOR in torch-xpu-ops if it does not exist yet:

bash
# Check if milestone exists; create if not
gh api repos/intel/torch-xpu-ops/milestones --jq '.[] | select(.title == "PTMAJOR_MINOR") | .title' \
  || gh api repos/intel/torch-xpu-ops/milestones -f title="PTMAJOR_MINOR" -f state=open

Open the tracker issue with this exact body template:

Title: [VERSION] Release Tracker
Milestone: PTMAJOR_MINOR

Issue body (replace placeholders):

markdown
We cut a [release branch](https://github.com/intel/torch-xpu-ops/tree/BRANCH) for the MAJOR_MINOR.0 release.

Our plan from this point is roughly:

- Phase 1 (until <PHASE1_DEADLINE>): work on finalizing the release branch

- Phase 2 (after <PHASE2_START>): perform extended integration/stability/performance testing based on Release Candidate builds.

This issue is for tracking cherry-picks to the release branch.

Refer <PYTORCH_TRACKER_URL>

Where:

  • <PHASE1_DEADLINE> / <PHASE2_START> come from the pytorch tracker (Step 1)
  • <PYTORCH_TRACKER_URL> is https://github.com/pytorch/pytorch/issues/<NUMBER>
bash
gh issue create -R intel/torch-xpu-ops \
  --title "[VERSION] Release Tracker" \
  --milestone "PTMAJOR_MINOR" \
  --body "$(cat <<'EOF'
<body from template above>
EOF
)"

Record the created issue number for Step 5.

Step 4 — Create Release-Only Changes PR

This PR changes the default branch parameters in workflow files from main to BRANCH.

4a. Create a working branch
bash
git fetch origin BRANCH
git checkout -b release_MAJOR_MINOR_change origin/BRANCH

(Branch naming convention: release_X.Y_change, e.g. release_2.12_change)

4b. Edit workflow files

Two files need updating — .github/workflows/_linux_build.yml and .github/workflows/_windows_ut.yml:

For each file, change the pytorch and torch_xpu_ops input defaults:

yaml
# Before
      pytorch:
        ...
        default: 'main'
        description: Pytorch main by default, ...
      torch_xpu_ops:
        ...
        default: 'main'
        description: Torch-xpu-ops main by default, ...

# After
      pytorch:
        ...
        default: 'BRANCH'
        description: Pytorch BRANCH by default, ...
      torch_xpu_ops:
        ...
        default: 'BRANCH'
        description: Torch-xpu-ops BRANCH by default, ...

Only change the default value and update main to BRANCH in the description string. Do not touch any other fields.

4c. Commit and push
bash
git add .github/workflows/_linux_build.yml .github/workflows/_windows_ut.yml
git commit -m "[RELEASE MAJOR_MINOR] Release only changes"
git push origin release_MAJOR_MINOR_change
4d. Open the PR
bash
gh pr create -R intel/torch-xpu-ops \
  --base BRANCH \
  --head release_MAJOR_MINOR_change \
  --title "[RELEASE MAJOR_MINOR] Release only changes"

No description body is needed.

Step 5 — Comment on Release Tracker Issue

Post the cherry-pick tracking comment on the torch-xpu-ops tracker issue created in Step 3:

bash
gh issue comment <ISSUE_NUMBER> -R intel/torch-xpu-ops --body "$(cat <<'EOF'
Link to landed trunk PR (if applicable):
* NA

Link to release branch PR:
* <PR_URL>

Criteria Category:
* Release only changes
EOF
)"

Where <PR_URL> is the URL from Step 4d.

Checklist

  • PyTorch release branch exists and tracker issue located
  • torch-xpu-ops release branch created from pinned commit
  • Release tracker issue created with correct milestone and dates
  • Workflow defaults PR opened against release branch
  • Tracker comment posted with PR link

© intel, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .claude/skills/release-branching of intel/torch-xpu-ops.

Open the folder on GitHubat commit a033aa5

Compare with similar skills

Release Branching 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.

Release Branching compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Release Branching this skillintel/torch-xpu-ops115—~1.4kAutomated safety check: PassApache-2.0
Add Uint Supportpytorch/pytorch104k2 repos~2.3kAutomated safety check: PassCustom licence
CLIP Image-Text MatchingOrchestra-Research/AI-Research-SKILLs13k8 repos~1.7kAutomated safety check: PassMIT
Add Torch Shapes Examplefacebook/pyrefly7.1k—~1.3kAutomated safety check: PassMIT
Interview Cheatsheetwanshuiyin/ARIS-in-AI-Offer5801 repos~3.4kAutomated safety check: NotesMIT
Ghstack CIpytorch/pytorch104k—~1.4kAutomated safety check: PassCustom licence

Similar skills

  • Add Uint Support

    pytorch/pytorch

    Add unsigned integer (uint) type support to PyTorch operators by updating ATDISPATCH macros.

    104k GitHub starsUsed in 2 repos~2.3k tokens
    AI & LLM EngineeringAuto-check passed
  • CLIP Image-Text Matching

    Orchestra-Research/AI-Research-SKILLs

    Explains OpenAI's CLIP model for zero-shot image classification, image-text similarity, semantic image search and content moderation, with install steps and code patterns.

    13k GitHub starsUsed in 8 repos~1.7k tokens
    AI & LLM EngineeringAuto-check passed
  • Add Torch Shapes Example

    facebook/pyrefly

    Official

    A skill your agent uses when adding a new PyTorch model to Pyrefly's shape-tracking example corpus under tensor-shapes/pyrefly-torch-stubs/examples — i.e.

    7.1k GitHub stars~1.3k tokensUpdated today
    AI & LLM EngineeringAuto-check passed
  • Interview Cheatsheet

    wanshuiyin/ARIS-in-AI-Offer

    Generate a long-form Chinese interview-prep cheat sheet on a specific ML/LLM topic — formulas with derivations, from-scratch PyTorch code, comparison tables, and 25 高频面试题 (L1 必会 / L2 进阶 / L3 顶级 lab).

    580 GitHub starsUsed in 1 repo~3.4k tokens
    AI & LLM EngineeringAuto-check: notes
  • Ghstack CI

    pytorch/pytorch

    Manage CI for PyTorch ghstack stacks by running CI where its results are useful now and deferring other PRs with [no-ci].

    104k GitHub stars~1.4k tokensUpdated today
    AI & LLM EngineeringAuto-check passed
  • MUSA GPU Training Optimizer

    open-infra-skills/infra-skills

    Profiles, benchmarks and tunes AI training workloads on Moore Threads MUSA GPUs with a measurement-first process that keeps model behavior unchanged.

    141 GitHub stars~1.7k tokensUpdated 3 mo ago
    AI & LLM EngineeringAuto-check passed

More from intel/torch-xpu-ops

All 29 skills in this repo
  • Intel GPU Device Selection

    intel/torch-xpu-ops

    Official

    Select the Intel GPU device to use when a system has multiple Intel GPU devices.

    115 GitHub stars~508 tokensUpdated today
    Auto-check passed
  • Xpu CI Health Check

    intel/torch-xpu-ops

    Official

    Check PyTorch ciflow/xpu (xpu.yml) on the main branch, collect the failing XPU test cases from the most recent completed run(s), analyze the ROOT CAUSE of each failure with AI, and produce a list…

    115 GitHub stars~1.5k tokensUpdated today
    Auto-check passed
  • At Dispatch V2

    intel/torch-xpu-ops

    Official

    Convert PyTorch ATDISPATCH macros to ATDISPATCHV2 format in ATen C++ code.

    115 GitHub starsUsed in 3 repos~2.2k tokens
    Auto-check passed
  • PR Review

    intel/torch-xpu-ops

    Official

    Review pull requests for XPU operator or backend code. An agent skill from intel/torch-xpu-ops.

    115 GitHub stars~4.2k tokensUpdated today
    Auto-check passed
  • Skill Writer

    intel/torch-xpu-ops

    Official

    Guide users through creating Agent Skills for Claude Code. An agent skill from intel/torch-xpu-ops.

    115 GitHub starsUsed in 3 repos~2.4k tokens
    Auto-check passed
  • Ut Issue Authoring

    intel/torch-xpu-ops

    Official

    Read the evidence a nightly UT run produced, decide which failures share a root cause and which are machine breakage rather than product bugs, and write one issue draft per root cause to drafts.json.

    115 GitHub stars~2k tokensUpdated today
    Auto-check passed

Works with

Questions about Release Branching

What does Release Branching do?

A skill your agent uses when setting up a new torch-xpu-ops release branch corresponding to a PyTorch release. Release Branching is an agent skill from intel/torch-xpu-ops, published by the product's own GitHub organization. Use when setting up a new torch-xpu-ops release branch corresponding to a PyTorch release.

When should I use Release Branching?

Release Branching fits situations like: setting up a new torch-xpu-ops release branch corresponding to a PyTorch release; tasks that involve Deep learning.

How do I install Release Branching in Claude Code?

Run `npx skills add intel/torch-xpu-ops --skill release-branching -a claude-code`. Or copy the skill folder (.claude/skills/release-branching in intel/torch-xpu-ops) into .claude/skills/release-branching in your project. Claude Code loads it when a task matches its description.

How do I install Release Branching in Codex?

Run `npx skills add intel/torch-xpu-ops --skill release-branching -a codex`. Or copy the skill folder (.claude/skills/release-branching in intel/torch-xpu-ops) into .agents/skills/release-branching in your project. Codex loads it when a task matches its description.

Can I use Release Branching 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 intel/torch-xpu-ops --skill release-branching -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/release-branching, .gemini/skills/release-branching, .github/skills/release-branching and .opencode/skills/release-branching in your project.

What does Release Branching need to run?

Going by SKILL.md and its folder, Release Branching needs the command-line tools its instructions call (gh and git).

Does Release Branching access the network?

SKILL.md names 1 domain. In commands or code: github.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Release Branching 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 Release Branching use?

Release Branching 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 Release Branching use?

About 1.4k tokens (SKILL.md is roughly 5.7k 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 Release Branching?

Skills that share tags, products or a category with Release Branching: Add Uint Support (pytorch/pytorch, 104k stars), CLIP Image-Text Matching (Orchestra-Research/AI-Research-SKILLs, 13k stars), Add Torch Shapes Example (facebook/pyrefly, 7.1k stars) and Interview Cheatsheet (wanshuiyin/ARIS-in-AI-Offer, 580 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Release Branching?

intel (a GitHub organization, an official publisher) maintains it in intel/torch-xpu-ops, which has 115 GitHub stars. The repository holds 29 skills in this directory. The repository was last updated on October 8, 2026.

Source: intel/torch-xpu-ops on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.