pr-retro

boshu2/agentops · updated Apr 8, 2026

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$npx skills add https://github.com/boshu2/agentops --skill pr-retro
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summary

Learn from PR outcomes by analyzing accept/reject patterns.

skill.md

PR Retro Skill

Learn from PR outcomes by analyzing accept/reject patterns.

Overview

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:

  • After a PR is merged (capture success patterns)
  • After a PR is rejected (understand why)
  • After receiving significant review feedback
  • Periodically to review contribution patterns

Workflow

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

Phase 1: PR Discovery

# 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

Phase 2: Outcome Analysis

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

Phase 3: Feedback Extraction

# 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")'

Feedback Categories

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

Phase 4: Pattern Identification

Success Patterns (If Merged)

What Worked Evidence
Small, focused PR < 5 files
Followed conventions No style comments
Good tests No "add tests" requests
Clear description Quick approval

Failure Patterns (If Rejected)

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"

Phase 5: Lesson Extraction

Lesson Template

## Lesson: [Title]

**Context**: [When does this apply?]
**Learning**: [What did we learn?]
**Action**: [What to do differently?]

**Evidence**:
- PR #N: [quote or summary]

Common Lessons

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

Phase 6: Output

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}

Anti-Patterns

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

Examples

Learn From Rejected PR

User says: "Run a retro on why this PR was rejected."

What happens:

  1. Analyze reviewer feedback and timeline.
  2. Identify preventable process and scope issues.
  3. Capture reusable lessons for future PRs.

Learn From Successful Merge

User says: "Extract what worked from this merged PR."

What happens:

  1. Identify patterns that sped review/approval.
  2. Distill actionable playbook updates.
  3. Save lessons for future contribution flows.

Troubleshooting

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
how to use pr-retro

How to use pr-retro 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-retro
2

Execute installation command

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

$npx skills add https://github.com/boshu2/agentops --skill pr-retro

The skills CLI fetches pr-retro from GitHub repository boshu2/agentops 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-retro

Reload or restart Cursor to activate pr-retro. Access the skill through slash commands (e.g., /pr-retro) 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

4.561 reviews
  • Dhruvi Jain· Dec 24, 2024

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

  • Carlos Harris· Dec 24, 2024

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

  • Pratham Ware· Dec 20, 2024

    I recommend pr-retro for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Henry Abebe· Dec 20, 2024

    I recommend pr-retro for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Aarav Patel· Dec 12, 2024

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

  • Charlotte Nasser· Dec 8, 2024

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

  • Aanya Harris· Dec 4, 2024

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

  • William Shah· Dec 4, 2024

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

  • Amelia Desai· Nov 27, 2024

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

  • Hana Sethi· Nov 23, 2024

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

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