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pr-draft-summary

Prepare an English pull request title, description, and branch suggestion from completed local changes. It reviews Git changes, includes untracked files, and formats issue references so the draft is ready to paste into GitHub.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

Prepare the required local PR title, description, and branch suggestion after eligible implementation work is complete.

설치 방법 보기

이럴 때 유용합니다

  • Drafting a pull request after implementation
  • Summarizing uncommitted changes and new files
  • Preparing branch names and issue references

포함된 파일(2)

  • SKILL.md7.0 KB
  • agents/openai.yaml251 B

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

PR Draft Summary

Purpose

Produce the PR-ready summary required in this repository after eligible code work is complete: a concise summary plus a PR-ready title and draft description that begins with "This pull request <verb> ...". The block should be ready to paste into a PR for openai-agents-python.

When to Trigger

  • An explicit user request for a PR draft takes precedence over the automatic-trigger exclusions below.
  • For automatic invocation, spelling, comments, or formatting alone are editorial even under runtime/test paths when they change no behavior or contract. Skip the automatic draft for those edits.
  • Before every final response, check whether the current task changed runtime code (src/agents/), tests (tests/), examples (examples/), build/test configuration, or docs with behavior impact.
  • If it did, run this skill after required verification and before sending the final response. Do not use perceived change size to decide whether to run it.
  • Run it for eligible local-only and uncommitted work even when the user did not ask to create a pull request. Producing this text does not authorize creating a branch, committing, pushing, or opening a pull request.
  • Skip only for trivial or conversation-only tasks, repo-meta/doc-only tasks without behavior impact, an explicitly invoked $release-candidate-prep handoff that uses the complete $final-release-review report as its release-specific PR description, or when the user explicitly says not to include the PR draft block. This exception applies to preparing the release candidate itself, not to implementing or changing the release-preparation skill.

Inputs to Collect Automatically (do not ask the user)

  • Current branch: git rev-parse --abbrev-ref HEAD.
  • Working tree: git status -sb.
  • Untracked files: git ls-files --others --exclude-standard (use with git status -sb to ensure they are surfaced; --stat does not include them).
  • Changed files: git diff --name-only (unstaged) and git diff --name-only --cached (staged); sizes via git diff --stat and git diff --stat --cached.
  • Latest release tag (prefer remote-aware lookup): LATEST_RELEASE_TAG=$(.agents/skills/final-release-review/scripts/find_latest_release_tag.sh origin 'v*' 2>/dev/null || git tag -l 'v*' --sort=-v:refname | head -n1).
  • Base reference (use the branch's upstream, fallback to origin/main):
    • BASE_REF=$(git rev-parse --abbrev-ref --symbolic-full-name @{upstream} 2>/dev/null || echo origin/main).
    • BASE_COMMIT=$(git merge-base --fork-point "$BASE_REF" HEAD || git merge-base "$BASE_REF" HEAD || echo "$BASE_REF").
  • Commits ahead of the base fork point: git log --oneline --no-merges ${BASE_COMMIT}..HEAD.
  • Category signals for this repo: runtime (src/agents/), tests (tests/), examples (examples/), docs (docs/, mkdocs.yml), build/test config (pyproject.toml, uv.lock, Makefile, .github/).

Workflow

  1. Run the commands above without asking the user; compute BASE_REF/BASE_COMMIT first so later commands reuse them.
  2. If there are no staged/unstaged/untracked changes and no commits ahead of ${BASE_COMMIT}, reply briefly that no code changes were detected and skip emitting the PR block.
  3. Infer change type from the touched paths listed under "Category signals"; classify as feature, fix, refactor, or docs-with-impact, and flag backward-compatibility risk only when the diff changes released public APIs, external config, persisted data, serialized state, or wire protocols. Judge that risk against LATEST_RELEASE_TAG, not unreleased branch-only churn.
  4. Summarize changes in 1–3 short sentences using the key paths (top 5) and git diff --stat output; explicitly call out untracked files from git status -sb/git ls-files --others --exclude-standard because --stat does not include them. If the working tree is clean but there are commits ahead of ${BASE_COMMIT}, summarize using those commit messages.
  5. Choose the lead verb for the description: feature → adds, bug fix → fixes, refactor/perf → improves or updates, docs-only → updates.
  6. Suggest a branch name. If already off main, keep it; otherwise propose feat/<slug>, fix/<slug>, or docs/<slug> based on the primary area (e.g., docs/pr-draft-summary-guidance).
  7. If the current branch matches issue-<number> (digits only), keep that branch suggestion. Optionally pull light issue context (for example via the GitHub API) when available, but do not block or retry if it is not. When an issue number is present, use the native same-repository reference #<number> and include an auto-closing line such as This pull request resolves #<number>.. Do not add the explicit issue URL or wrap the reference in a Markdown link.
  8. Draft the PR title and description using the template below. Apply the repository-wide GitHub paste-readiness rule: use exactly #123 for same-repository issues or PRs and owner/repo#123 for cross-repository references; never emit [PR #123](https://github.com/owner/repo/pull/123), [#123](...), Codex navigation links, local file links, Codex-only citation markers or footnotes, or app directives in the copy-ready block. Preserve ordinary descriptive links to API docs, design notes, and other targets without native GitHub issue or pull-request syntax.
  9. Normalize references before returning the block: replace every same-repository URL or openai/openai-agents-python#<number> reference with #<number>, replace every cross-repository issue or pull-request URL with owner/repo#<number>, then rescan the full block. Do not return it while a Markdown-linked issue or pull-request label, a same-repository qualified reference, or a bare GitHub issue or pull-request URL remains.
  10. Output only the block in "Output Format". Keep any surrounding status note minimal and in English.

Output Format

When closing out a task, add this concise Markdown block (English only) after any brief status note unless the task falls under the documented skip cases or the user says they do not want it.

# Pull Request Draft

## Branch name suggestion

git checkout -b <kebab-case suggestion, e.g., feat/pr-draft-summary-skill>

## Title

<single-line imperative title, which can be a commit message; if a common prefix like chore: and feat: etc., having them is preferred>

## Description

<include what you changed plus a draft pull request title and description for your local changes; start the description with prose such as "This pull request resolves/updates/adds ..." using a verb that matches the change (you can use bullets later), explain the change background (for bugs, clearly describe the bug, symptoms, or repro; for features, what is needed and why), any behavior changes or considerations to be aware of, and you do not need to mention tests you ran.>

Keep it tight—no redundant prose around the block, and avoid repeating details between Changes and the description. Tests do not need to be listed unless specifically requested.

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한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

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Analyze CSV files with Python and get concise numerical summaries. The skill checks column structure before calculating requested aggregates, includes units when available, and explains assumptions when data is missing or incorrectly formatted.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

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docs-sync

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Review logs and source files from a completed manual example run. Check that results are current and complete, verify intended behavior beyond successful exit codes, and distinguish product defects from environment or credential problems.

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  • Review results after a manual example run
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