Learn from PR outcomes by analyzing accept/reject patterns.
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Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionpr-retroExecute the skills CLI command in your project's root directory to begin installation:
Fetches pr-retro from boshu2/agentops and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate pr-retro. Access via /pr-retro in your agent's command palette.
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.
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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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Learn from PR outcomes by analyzing accept/reject patterns.
After a PR is merged or rejected, analyze what worked and what didn't to improve future contributions.
Output: .agents/learnings/YYYY-MM-DD-pr-{repo}-{outcome}.md
When to Use:
1. PR Discovery -> Find the PR to analyze
2. Outcome Analysis -> Merged/rejected/changes requested
3. Feedback Extraction -> What did reviewers say?
4. Pattern Identification -> What worked/didn't
5. Lesson Extraction -> Reusable learnings
6. Output -> Write retro document
# If PR number provided
gh pr view <number> --json state,reviews,comments,mergedAt,closedAt
# Find recent PRs by you
gh pr list --state all --author @me --limit 10
# Find PRs to a specific repo
gh pr list -R <owner/repo> --state all --author @me --limit 10
| Outcome | Meaning | Focus |
|---|---|---|
| Merged | Success | What worked? |
| Closed (not merged) | Rejected | Why? |
| Open (stale) | Ignored/abandoned | What went wrong? |
| Changes requested | Needs work | What feedback? |
# Get PR outcome
gh pr view <number> --json state,mergedAt,closedAt,reviews
# Get all review comments
gh pr view <number> --json reviews --jq '.reviews[] | "\(.author.login): \(.body)"'
# Get all comments
gh api repos/<owner>/<repo>/pulls/<number>/comments --jq '.[].body'
# Get requested changes
gh pr view <number> --json reviews --jq '.reviews[] | select(.state == "CHANGES_REQUESTED")'
| Category | Examples |
|---|---|
| Style | Naming, formatting, conventions |
| Technical | Algorithm, architecture, patterns |
| Scope | Too big, scope creep, unrelated changes |
| Testing | Missing tests, coverage, edge cases |
| Documentation | Missing docs, unclear comments |
| Process | Wrong branch, missing sign-off |
| What Worked | Evidence |
|---|---|
| Small, focused PR | < 5 files |
| Followed conventions | No style comments |
| Good tests | No "add tests" requests |
| Clear description | Quick approval |
| What Failed | Evidence |
|---|---|
| Too large | "Please split this PR" |
| Scope creep | "This is out of scope" |
| Missing tests | "Please add tests" |
| Wrong approach | "Consider using X instead" |
## Lesson: [Title]
**Context**: [When does this apply?]
**Learning**: [What did we learn?]
**Action**: [What to do differently?]
**Evidence**:
- PR #N: [quote or summary]
| Lesson | Action |
|---|---|
| PR too large | Split PRs under 200 lines |
| Missing context | Add "## Context" section |
| Style mismatch | Run linter before PR |
| Missing tests | Add tests for new code |
| Slow review | Ping after 1 week |
Write to .agents/learnings/YYYY-MM-DD-pr-{repo}-{outcome}.md
# PR Retro: {repo} #{number}
**Date**: YYYY-MM-DD
**PR**: {url}
**Outcome**: Merged / Rejected / Stale
## Summary
{What was the PR about? What happened?}
## Timeline
| Date | Event |
|------|-------|
| {date} | PR opened |
| {date} | First review |
| {date} | {outcome} |
## Feedback Analysis
### Positive Feedback
- {quote}
### Requested Changes
- {quote}
### Rejection Reasons (if applicable)
- {quote}
## Lessons Learned
### Lesson 1: {title}
**Context**: {when this applies}
**Learning**: {what we learned}
**Action**: {what to do differently}
## Updates to Process
{Any changes to make to pr-prep, pr-plan, or other skills}
## Next Steps
{Future actions based on this retro}
| DON'T | DO INSTEAD |
|---|---|
| Skip retros on merged PRs | Learn from success too |
| Blame maintainers | Focus on what YOU can change |
| Generic lessons | Specific, actionable learnings |
| Skip rejected PRs | Most valuable learning source |
User says: "Run a retro on why this PR was rejected."
What happens:
User says: "Extract what worked from this merged PR."
What happens:
| Problem | Cause | Solution |
|---|---|---|
| Retro is generic | Feedback not tied to evidence | Cite specific comments/decisions and outcomes |
| No clear lesson extracted | Analysis stayed descriptive | Convert observations into behavior changes |
| Maintainer signal is mixed | Contradictory review comments | Separate hard blockers from preference feedback |
| Process changes not adopted | Lessons not operationalized | Add explicit updates to prep/plan/validate workflow |
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
✓ Do
✗ Don't
💡 Pro Tips
✓ 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.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
pproenca/dot-skills
ailabs-393/ai-labs-claude-skills
mattpocock/skills
pr-retro is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
pr-retro reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend pr-retro for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
I recommend pr-retro for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
pr-retro has been reliable in day-to-day use. Documentation quality is above average for community skills.
Registry listing for pr-retro matched our evaluation — installs cleanly and behaves as described in the markdown.
pr-retro fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Keeps context tight: pr-retro is the kind of skill you can hand to a new teammate without a long onboarding doc.
pr-retro fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Registry listing for pr-retro matched our evaluation — installs cleanly and behaves as described in the markdown.
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