pr-draft-summary

openai/openai-agents-python · updated Apr 8, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$npx skills add https://github.com/openai/openai-agents-python --skill pr-draft-summary
0 commentsdiscussion
summary

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

skill.md

PR Draft Summary

Purpose

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

When to Trigger

  • The task for this repo is finished (or ready for review) and it touched runtime code, tests, examples, docs with behavior impact, or build/test configuration.
  • Treat this as the default final handoff step for substantive code work. Run it after any required verification or changeset work and before sending the "work complete" response.
  • Skip only for trivial or conversation-only tasks, repo-meta/doc-only tasks without behavior impact, or when the user explicitly says not to include the PR draft block.

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, reference https://github.com/openai/openai-agents-python/issues/<number> and include an auto-closing line such as This pull request resolves #<number>..
  8. Draft the PR title and description using the template below.
  9. 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.

how to use pr-draft-summary

How to use pr-draft-summary on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add pr-draft-summary
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/openai/openai-agents-python --skill pr-draft-summary

The skills CLI fetches pr-draft-summary from GitHub repository openai/openai-agents-python and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/pr-draft-summary

Reload or restart Cursor to activate pr-draft-summary. Access the skill through slash commands (e.g., /pr-draft-summary) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.752 reviews
  • Sophia Srinivasan· Dec 24, 2024

    We added pr-draft-summary from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Michael Bhatia· Dec 24, 2024

    pr-draft-summary is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Pratham Ware· Dec 16, 2024

    Keeps context tight: pr-draft-summary is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Noah Haddad· Dec 8, 2024

    pr-draft-summary reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Kiara Anderson· Nov 27, 2024

    We added pr-draft-summary from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Kaira Jackson· Nov 15, 2024

    pr-draft-summary reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Yash Thakker· Nov 7, 2024

    pr-draft-summary has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Dhruvi Jain· Oct 26, 2024

    Solid pick for teams standardizing on skills: pr-draft-summary is focused, and the summary matches what you get after install.

  • Sophia Sharma· Oct 18, 2024

    pr-draft-summary fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Sofia Kim· Oct 6, 2024

    Registry listing for pr-draft-summary matched our evaluation — installs cleanly and behaves as described in the markdown.

showing 1-10 of 52

1 / 6