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.
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Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionpr-draft-summaryExecute the skills CLI command in your project's root directory to begin installation:
Fetches pr-draft-summary from openai/openai-agents-python and configures it for Cursor.
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Confirm successful installation by checking the skill directory location:
Restart Cursor to activate pr-draft-summary. Access via /pr-draft-summary in your agent's command palette.
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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
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
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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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.
git rev-parse --abbrev-ref HEAD.git status -sb.git ls-files --others --exclude-standard (use with git status -sb to ensure they are surfaced; --stat does not include them).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=$(.agents/skills/final-release-review/scripts/find_latest_release_tag.sh origin 'v*' 2>/dev/null || git tag -l 'v*' --sort=-v:refname | head -n1).origin/main):
BASE_REF=$(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").git log --oneline --no-merges ${BASE_COMMIT}..HEAD.src/agents/), tests (tests/), examples (examples/), docs (docs/, mkdocs.yml), build/test config (pyproject.toml, uv.lock, Makefile, .github/).BASE_REF/BASE_COMMIT first so later commands reuse them.${BASE_COMMIT}, reply briefly that no code changes were detected and skip emitting the PR block.LATEST_RELEASE_TAG, not unreleased branch-only churn.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.adds, bug fix β fixes, refactor/perf β improves or updates, docs-only β updates.feat/<slug>, fix/<slug>, or docs/<slug> based on the primary area (e.g., docs/pr-draft-summary-guidance).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>..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 tightβno redundant prose around the block, and avoid repeating details between Changes and the description. Tests do not need to be listed unless specifically requested.
Make data-driven prioritization decisions faster
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
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
β Do
β Don't
π‘ Pro Tips
β Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
β 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.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
pproenca/dot-skills
ailabs-393/ai-labs-claude-skills
mattpocock/skills
We added pr-draft-summary from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
pr-draft-summary is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Keeps context tight: pr-draft-summary is the kind of skill you can hand to a new teammate without a long onboarding doc.
pr-draft-summary reduced setup friction for our internal harness; good balance of opinion and flexibility.
We added pr-draft-summary from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
pr-draft-summary reduced setup friction for our internal harness; good balance of opinion and flexibility.
pr-draft-summary has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: pr-draft-summary is focused, and the summary matches what you get after install.
pr-draft-summary fits our agent workflows well β practical, well scoped, and easy to wire into existing repos.
Registry listing for pr-draft-summary matched our evaluation β installs cleanly and behaves as described in the markdown.
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