debugger▌
charon-fan/agent-playbook · updated Apr 8, 2026
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An advanced debugging specialist that helps diagnose and resolve code issues systematically.
Debugger
An advanced debugging specialist that helps diagnose and resolve code issues systematically.
When This Skill Activates
Activates when you:
- Report an error or bug
- Mention "debug this" or "help debug"
- Describe unexpected behavior
- Ask why something isn't working
Debugging Process
Phase 1: Understand the Problem
-
Reproduce the issue
- What are the exact steps to reproduce?
- What is the expected behavior?
- What is the actual behavior?
- What error messages appear?
-
Gather context
# Check recent changes git log --oneline -10 # Check error logs tail -f logs/error.log # Check environment env | grep -i debug
Phase 2: Isolate the Issue
-
Locate the error source
- Stack trace analysis
- Error code lookup
- Log correlation
-
Narrow down scope
- Binary search (comment out half)
- Minimize reproduction case
- Identify affected components
Phase 3: Analyze the Root Cause
Common Error Categories
| Category | Symptoms | Investigation Steps |
|---|---|---|
| Null/Undefined | "Cannot read X of undefined" | Trace the variable origin |
| Type Errors | "X is not a function" | Check actual vs expected type |
| Async Issues | Race conditions, timing | Check promise handling, async/await |
| State Issues | Stale data, wrong state | Trace state mutations |
| Network | Timeouts, connection refused | Check endpoints, CORS, auth |
| Environment | Works locally, not in prod | Compare env vars, versions |
| Memory | Leaks, OOM | Profile memory usage |
| Concurrency | Deadlocks, race conditions | Check locks, shared state |
Phase 4: Form Hypotheses
For each potential cause:
- Form a hypothesis
- Create a test to validate
- Run the test
- Confirm or reject
Phase 5: Fix and Verify
- Implement the fix
- Add logging if needed
- Test the fix
- Add regression test
Debugging Commands
General Debugging
# Find recently modified files
find . -type f -mtime -1 -name "*.js" -o -name "*.ts" -o -name "*.py"
# Grep for error patterns
grep -r "ERROR\|FATAL\|Exception" logs/
# Search for suspicious patterns
grep -r "TODO\|FIXME\|XXX" src/
# Check for console.log left in code
grep -r "console\.log\|debugger" src/
Language-Specific
JavaScript/TypeScript:
# Run with debug output
NODE_DEBUG=* node app.js
# Check syntax
node -c file.js
# Run tests in debug mode
npm test -- --inspect-brk
Python:
# Run with pdb
python -m pdb script.py
# Check syntax
python -m py_compile script.py
# Verbose mode
python -v script.py
Go:
# Race detection
go run -race main.go
# Debug build
go build -gcflags="-N -l"
# Profile
go test -cpuprofile=cpu.prof
Common Debugging Patterns
Pattern 1: Divide and Conquer
# When you don't know where the bug is:
def process():
step1()
step2()
step3()
step4()
# Comment out half:
def process():
step1()
# step2()
# step3()
# step4()
# If bug disappears, uncomment half of commented:
def process():
step1()
step2()
# step3()
# step4()
# Continue until you isolate the bug
Pattern 2: Add Logging
// Before (mysterious failure):
async function getUser(id: string) {
const user = await db.find(id);
return transform(user);
}
// After (with logging):
async function getUser(id: string) {
console.log('[DEBUG] getUser called with id:', id);
const user = await db.find(id);
console.log('[DEBUG] db.find returned:', user);
const result = transform(user);
console.log('[DEBUG] transform returned:', result);
return result;
}
Pattern 3: Minimal Reproduction
// Complex code with bug:
function processBatch(items, options) {
// 100 lines of complex logic
}
// Create minimal reproduction:
function processBatch(items, options) {
console.log('Items:', items.length);
console.log('Options:', options);
// Test with minimal data
return processBatch([items[0]], options);
}
Error Message Analysis
Common Error Messages
| Error | Likely Cause | Solution |
|---|---|---|
Cannot read property 'X' of undefined |
Accessing property on null/undefined | Add null check, use optional chaining |
X is not a function |
Wrong type, shadowing | Check typeof, verify import |
Unexpected token |
Syntax error | Check line before error, validate syntax |
Module not found |
Import path wrong | Check relative path, verify file exists |
EADDRINUSE |
Port already in use | Kill existing process, use different port |
Connection refused |
Service not running | Start service, check port |
Timeout |
Request too slow | Increase timeout, check network |
Debugging Checklist
- I can reproduce the issue consistently
- I have identified the exact error location
- I understand the root cause
- I have a proposed fix
- The fix doesn't break existing functionality
- I've added a test to prevent regression
Scripts
Generate a debug report:
python scripts/debug_report.py <error-message>
References
references/checklist.md- Debugging checklistreferences/patterns.md- Common debugging patternsreferences/errors.md- Error message reference
How to use debugger on Cursor
AI-first code editor with Composer
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 debugger
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches debugger from GitHub repository charon-fan/agent-playbook and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate debugger. Access the skill through slash commands (e.g., /debugger) 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
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.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 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▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
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Ratings
4.6★★★★★57 reviews- ★★★★★Kofi Brown· Dec 28, 2024
Solid pick for teams standardizing on skills: debugger is focused, and the summary matches what you get after install.
- ★★★★★Xiao Shah· Dec 28, 2024
We added debugger from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Evelyn Rao· Dec 28, 2024
debugger reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Chaitanya Patil· Dec 8, 2024
debugger has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Yuki Li· Dec 4, 2024
Useful defaults in debugger — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Kofi Torres· Dec 4, 2024
I recommend debugger for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Piyush G· Nov 27, 2024
debugger reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Maya Jain· Nov 23, 2024
Solid pick for teams standardizing on skills: debugger is focused, and the summary matches what you get after install.
- ★★★★★Soo Kim· Nov 19, 2024
I recommend debugger for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Xiao Desai· Nov 19, 2024
debugger fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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