bug-fix

bobmatnyc/claude-mpm-skills · 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/bobmatnyc/claude-mpm-skills --skill bug-fix
0 commentsdiscussion
summary

Systematic workflow for verifying bug fixes to ensure quality and prevent regressions.

skill.md

Bug Fix Verification

Systematic workflow for verifying bug fixes to ensure quality and prevent regressions.

When to Use This Skill

Use this skill when:

  • Fixing a reported bug
  • Creating PR for bug fix
  • Need to document bug fix verification
  • Want to ensure fix doesn't introduce regressions
  • Need structured approach to bug resolution

Why Bug Fix Verification Matters

Problems It Solves

  • ❌ Fixing symptoms instead of root cause
  • ❌ Introducing new bugs while fixing old ones
  • ❌ Incomplete testing of edge cases
  • ❌ No proof that bug is actually fixed
  • ❌ Poor documentation of fix reasoning

Benefits

  • ✅ Confirms bug is truly fixed (not masked)
  • ✅ Documents root cause analysis
  • ✅ Prevents regression with tests
  • ✅ Provides clear evidence for stakeholders
  • ✅ Improves team knowledge of codebase

Bug Fix Workflow

Step 1: Reproduce Before Fix

Critical: Never fix a bug without first reproducing it.

Reproduction Checklist

  • Document exact steps to reproduce
  • Capture error message/behavior with screenshots
  • Note frequency (100% reproducible, intermittent, etc.)
  • Video recording if UI-related or complex interaction
  • Identify affected versions/environments
  • Note any workarounds users have found
  • Verify bug exists in clean environment (not just local)

Reproduction Documentation Template

## Bug Reproduction

### Steps to Reproduce
1. Navigate to `/dashboard`
2. Click "Export Data" button
3. Select date range: Jan 1 - Dec 31
4. Click "Generate Report"

### Expected Behavior
- Report downloads as CSV file
- File contains all transactions for date range
- Download completes in < 5 seconds

### Actual Behavior
- Error appears: "Failed to generate report"
- Console error: `TypeError: Cannot read property 'map' of undefined`
- No file downloads
- Issue occurs 100% of the time

### Environment
- Browser: Chrome 120.0.6099.109
- OS: macOS 14.2
- User Role: Admin
- Data Size: ~10,000 transactions

### Screenshots
![Error message](screenshots/export-error.png)
![Console error](screenshots/console-error.png)

Step 2: Root Cause Analysis

Investigate WHY the bug occurs, not just WHAT happens.

Investigation Steps

  1. Review Error Logs: Check server logs, browser console, error tracking
  2. Trace Code Path: Follow execution from trigger point to error
  3. Identify Breaking Point: Find exact line/function where bug occurs
  4. Understand Context: Why does code behave this way?
  5. Check Recent Changes: Did recent commit introduce this?
  6. Review Related Code: Are there similar patterns elsewhere?

Root Cause Documentation

## Root Cause Analysis

### Investigation
- Error occurs in `generateReport()` function at line 45
- Function assumes `transactions` array always exists
- When date range returns no results, backend returns `null`
- Frontend doesn't handle `null` case, tries to call `.map()` on `null`

### Root Cause
- Missing null check before array operations
- Backend API doesn't return consistent data structure (sometimes `[]`, sometimes `null`)
- No validation of API response shape

### Why This Wasn't Caught
- Unit tests only covered happy path (data exists)
- Integration tests didn't test empty result scenario
- Backend inconsistency not documented in API contract

Step 3: Implement Fix

Fix the root cause, not the symptom.

Fix Guidelines

  • Minimal Change: Fix only what's necessary
  • Defensive Coding: Add validation/guards
  • Consistent Patterns: Follow existing error handling patterns
  • Type Safety: Use types to prevent similar bugs
  • Documentation: Comment non-obvious fixes

Example Fix

// BEFORE (Bug)
function generateReport(transactions) {
  return transactions.map(t => ({
    date: t.date,
    amount: t.amount,
  }));
}

// AFTER (Fixed)
function generateReport(transactions) {
  // Guard against null/undefined from backend
  if (!transactions || !Array.isArray(transactions)) {
    console.warn('No transactions to export');
    return [];
  }

  return transactions.map(t => ({
    date: t.date,
    amount: t.amount,
  }));
}

Step 4: Verify Fix

Prove the bug is fixed through systematic testing.

Verification Checklist

  • Follow same reproduction steps
  • Confirm bug no longer occurs
  • Test edge cases around the fix
  • Verify no new errors introduced
  • Check fix works across environments (dev, staging)
  • Validate fix matches expected behavior

Verification Documentation

## Fix Verification

### Testing Performed
1. ✅ Followed original reproduction steps - bug no longer occurs
2. ✅ Tested with empty date range - shows "No data to export" message
3. ✅ Tested with valid date range - exports successfully
4. ✅ Tested with large dataset (50k+ transactions) - works correctly
5. ✅ Tested in Chrome, Firefox, Safari - all working
6. ✅ Tested on staging environment - fix confirmed

### Edge Cases Tested
- Empty result set → Shows appropriate message
- Null response from API → Handled gracefully
- Single transaction → Exports correctly
- Malformed transaction data → Logs error, doesn't crash

### No New Issues
- ✅ No console errors
- ✅ No memory leaks
- ✅ No performance degradation
- ✅ Other export features still work

Step 5: Add Tests to Prevent Regression

Critical: Every bug fix must include tests.

Test Requirements

  • Test that reproduces original bug (should pass after fix)
  • Tests for edge cases discovered during investigation
  • Integration test if bug involved multiple components
  • Update existing tests if they need to handle new scenarios

Example Tests

describe('generateReport', () => {
  // Test that reproduces original bug
  it('should handle null transactions gracefully', () => {
    const result = generateReport(null);
    expect(result).toEqual([]);
    expect(console.warn).toHaveBeenCalledWith('No transactions to export');
  });

  // Edge cases
  it('should handle undefined transactions', () => {
    const result = generateReport(undefined);
    expect(result).toEqual([]);
  });

  it('should handle empty array', () => {
    const result = generateReport([]);
    expect(result).toEqual([]);
  });

  it('should handle single transaction', () => {
    const transactions = [{ date: '2025-01-01', amount: 100 }];
    const result = generateReport(transactions);
    expect(result).toHaveLength(1);
    expect(result[0]).t
how to use bug-fix

How to use bug-fix 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 bug-fix
2

Execute installation command

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

$npx skills add https://github.com/bobmatnyc/claude-mpm-skills --skill bug-fix

The skills CLI fetches bug-fix from GitHub repository bobmatnyc/claude-mpm-skills 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/bug-fix

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

4.733 reviews
  • Liam Garcia· Dec 28, 2024

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

  • Diego Huang· Dec 20, 2024

    We added bug-fix from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Rahul Santra· Nov 23, 2024

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

  • Valentina Torres· Nov 11, 2024

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

  • Pratham Ware· Oct 14, 2024

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

  • Ira Khan· Oct 2, 2024

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

  • Sakshi Patil· Sep 17, 2024

    Useful defaults in bug-fix — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Zara Bhatia· Sep 17, 2024

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

  • Chaitanya Patil· Aug 8, 2024

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

  • Olivia Taylor· Aug 8, 2024

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

showing 1-10 of 33

1 / 4