mcpbeat

Fix Pr

pytorch/fix-pr

Address CI failures and unresolved review comments on a Helion pull request. Auto-activate when the user mentions a URL like https://github.com/pytorch/helion/pull/<number>.

745 tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
915
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/pytorch/helion --skill fix-pr

The instruction itself

5 sections, as written by the author

Fix a Helion pull request

Goal: bring a PR green by fixing CI failures and addressing unresolved review comments. Leave the fixes uncommitted and unstaged — the user handles committing and updating the PR.

1. Identify the target PR

Run git log -n1 to see the current commit. The local commit must correspond to the PR being fixed.

Resolve the PR number using whichever sources are available:

  • User-provided URL (e.g. https://github.com/pytorch/helion/pull/1234): extract the PR number directly.
  • Commit message stack-info line: look for a line of the form
  stack-info: PR: https://github.com/pytorch/helion/pull/<number>, branch: ...

Use the URL on that line. Ignore the branch: value — do not run any checkout, branch, or switch commands.

  • Both present: if the user-provided URL and the stack-info URL disagree, abort with an error.
  • Neither present: abort with an error explaining that the PR could not be identified.

Then fetch the PR metadata with gh pr view <number> --repo pytorch/helion --json title,body,.... Verify the PR title matches the local commit's subject line. If they differ, abort with an error — the local commit does not match the PR.

2. Fix CI failures

Use gh to list the PR's check runs and pull failure logs:

gh pr checks <number> --repo pytorch/helion
gh run view <run-id> --log-failed --repo pytorch/helion

For each failing check:

  • Infra failures (most commonly CUDA Compute Check, runner provisioning errors, transient network issues): do not attempt to fix. Note them and report at the end.
  • Real failures (lint, type-check, test failures, build errors): read the logs, locate the root cause, and fix it in the working tree. Re-run the relevant check locally when feasible (e.g. ./lint.sh, pytest <file>::<test>) to confirm the fix.

3. Address unresolved review comments

Fetch review comments and resolve any that haven't been addressed:

gh api repos/pytorch/helion/pulls/<number>/comments
gh api repos/pytorch/helion/pulls/<number>/reviews
gh pr view <number> --repo pytorch/helion --comments

For each unresolved comment, apply the requested change in the working tree. Skip comments that are already resolved, are non-actionable (praise, questions answered in thread), or that the author explicitly waved off.

4. Wrap up

  • Leave all fixes uncommitted and unstaged. Do not run git add, git commit, git push, or any rebase/checkout commands.
  • Report a short summary covering:
  • PR identified (number + title)
  • CI failures fixed (with file:line where useful)
  • Review comments addressed
  • Any infra failures skipped (so the user knows to retry them)
  • Anything that could not be fixed and why

How to use it

Copy the folder

Take pytorch/fix-pr from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.