
Debugging Strategies
- 10.6k installs
- 38.3k repo stars
- Updated July 22, 2026
- wshobson/agents
Systematic methodology and tools to identify root causes of bugs, performance issues, and unexpected behavior in running systems.
About
This skill teaches systematic debugging methodology combining the scientific method (observe, hypothesize, experiment, analyze) with practical tool usage across JavaScript, Python, and Go. Developers use it when tracking production issues, performance problems, memory leaks, or intermittent bugs that require structured investigation. Core workflows include reproducing issues consistently, gathering environment and error data, forming testable hypotheses, and isolating problems via binary search, differential debugging, or profiling. Covers Chrome DevTools, VS Code debugger, pdb, Delve, git bisect, heap snapshots, and performance profiling techniques.
- Four-phase systematic process: reproduce, gather information, form hypothesis, test and verify
- Language-specific debugger setups for JavaScript (Chrome DevTools, VS Code), Python (pdb, ipdb, cProfile), and Go (Delve
- Advanced techniques including git bisect for regressions, differential debugging, trace debugging, and memory leak detec
- Patterns for specific issue types: intermittent bugs (race conditions, timing), performance (profiling, N+1 queries), pr
- Scientific debugging mindset rejecting assumptions and emphasizing reproducibility, isolation, and detailed documentatio
Debugging Strategies by the numbers
- 10,629 all-time installs (skills.sh)
- +204 installs in the week ending Jul 28, 2026 (Skillselion tracking)
- Ranked #14 of 610 Debugging skills by installs in the Skillselion catalog
- Security screen: LOW risk (skills.sh audit)
- Data as of Jul 28, 2026 (Skillselion catalog sync)
debugging-strategies capabilities & compatibility
- Capabilities
- systematic reproduction and isolation · hypothesis formation and testing · binary search and differential debugging · language specific profiling and memory analysis · production debugging with safety constraints · performance bottleneck identification · race condition and timing issue detection
- Works with
- github · gitlab · sentry · datadog
- Use cases
- debugging · code review · testing
- Platforms
- macOS · Windows · Linux · WSL
- Runs
- Runs locally
- Pricing
- Free
What debugging-strategies says it does
Transform debugging from frustrating guesswork into systematic problem-solving with proven strategies, powerful tools, and methodical approaches.
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| Installs | 10.6k |
|---|---|
| repo stars | ★ 38.3k |
| Security audit | 3 / 3 scanners passed |
| Last updated | July 22, 2026 |
| Repository | wshobson/agents ↗ |
What it does
Systematically identify and fix bugs using methodical investigation, profiling tools, and root cause analysis across any codebase.
Who is it for?
Tracking production bugs, investigating performance issues, analyzing memory leaks, debugging distributed systems, understanding unfamiliar codebases, analyzing crash dumps
Skip if: Writing new features, architectural design, initial code development without runtime issues
When should I use this skill?
Bug reported, performance degradation observed, crash occurs, unexpected behavior in development or production, memory usage anomalies detected
What you get
Developers can efficiently reproduce issues, isolate problems to minimal cases, form and test hypotheses, and fix root causes using language-specific profiling and debugging tools.
- Reproducible bug case
- Root cause identified
- Isolated minimal example
By the numbers
- Covers debugging patterns for 3 major languages: JavaScript, Python, Go
- Provides 4 advanced debugging techniques: binary search, differential debugging, trace debugging, memory leak detection
- Includes systematic checklist of 12 common debugging mistakes to avoid
Files
Debugging Strategies
Transform debugging from frustrating guesswork into systematic problem-solving with proven strategies, powerful tools, and methodical approaches.
When to Use This Skill
- Tracking down elusive bugs
- Investigating performance issues
- Understanding unfamiliar codebases
- Debugging production issues
- Analyzing crash dumps and stack traces
- Profiling application performance
- Investigating memory leaks
- Debugging distributed systems
Core Principles
1. The Scientific Method
1. Observe: What's the actual behavior? 2. Hypothesize: What could be causing it? 3. Experiment: Test your hypothesis 4. Analyze: Did it prove/disprove your theory? 5. Repeat: Until you find the root cause
2. Debugging Mindset
Don't Assume:
- "It can't be X" - Yes it can
- "I didn't change Y" - Check anyway
- "It works on my machine" - Find out why
Do:
- Reproduce consistently
- Isolate the problem
- Keep detailed notes
- Question everything
- Take breaks when stuck
3. Rubber Duck Debugging
Explain your code and problem out loud (to a rubber duck, colleague, or yourself). Often reveals the issue.
Systematic Debugging Process
Phase 1: Reproduce
## Reproduction Checklist
1. **Can you reproduce it?**
- Always? Sometimes? Randomly?
- Specific conditions needed?
- Can others reproduce it?
2. **Create minimal reproduction**
- Simplify to smallest example
- Remove unrelated code
- Isolate the problem
3. **Document steps**
- Write down exact steps
- Note environment details
- Capture error messagesPhase 2: Gather Information
## Information Collection
1. **Error Messages**
- Full stack trace
- Error codes
- Console/log output
2. **Environment**
- OS version
- Language/runtime version
- Dependencies versions
- Environment variables
3. **Recent Changes**
- Git history
- Deployment timeline
- Configuration changes
4. **Scope**
- Affects all users or specific ones?
- All browsers or specific ones?
- Production only or also dev?Phase 3: Form Hypothesis
## Hypothesis Formation
Based on gathered info, ask:
1. **What changed?**
- Recent code changes
- Dependency updates
- Infrastructure changes
2. **What's different?**
- Working vs broken environment
- Working vs broken user
- Before vs after
3. **Where could this fail?**
- Input validation
- Business logic
- Data layer
- External servicesPhase 4: Test & Verify
## Testing Strategies
1. **Binary Search**
- Comment out half the code
- Narrow down problematic section
- Repeat until found
2. **Add Logging**
- Strategic console.log/print
- Track variable values
- Trace execution flow
3. **Isolate Components**
- Test each piece separately
- Mock dependencies
- Remove complexity
4. **Compare Working vs Broken**
- Diff configurations
- Diff environments
- Diff dataDebugging Tools
JavaScript/TypeScript Debugging
// Chrome DevTools Debugger
function processOrder(order: Order) {
debugger; // Execution pauses here
const total = calculateTotal(order);
console.log("Total:", total);
// Conditional breakpoint
if (order.items.length > 10) {
debugger; // Only breaks if condition true
}
return total;
}
// Console debugging techniques
console.log("Value:", value); // Basic
console.table(arrayOfObjects); // Table format
console.time("operation");
/* code */ console.timeEnd("operation"); // Timing
console.trace(); // Stack trace
console.assert(value > 0, "Value must be positive"); // Assertion
// Performance profiling
performance.mark("start-operation");
// ... operation code
performance.mark("end-operation");
performance.measure("operation", "start-operation", "end-operation");
console.log(performance.getEntriesByType("measure"));VS Code Debugger Configuration:
// .vscode/launch.json
{
"version": "0.2.0",
"configurations": [
{
"type": "node",
"request": "launch",
"name": "Debug Program",
"program": "${workspaceFolder}/src/index.ts",
"preLaunchTask": "tsc: build - tsconfig.json",
"outFiles": ["${workspaceFolder}/dist/**/*.js"],
"skipFiles": ["<node_internals>/**"]
},
{
"type": "node",
"request": "launch",
"name": "Debug Tests",
"program": "${workspaceFolder}/node_modules/jest/bin/jest",
"args": ["--runInBand", "--no-cache"],
"console": "integratedTerminal"
}
]
}Python Debugging
# Built-in debugger (pdb)
import pdb
def calculate_total(items):
total = 0
pdb.set_trace() # Debugger starts here
for item in items:
total += item.price * item.quantity
return total
# Breakpoint (Python 3.7+)
def process_order(order):
breakpoint() # More convenient than pdb.set_trace()
# ... code
# Post-mortem debugging
try:
risky_operation()
except Exception:
import pdb
pdb.post_mortem() # Debug at exception point
# IPython debugging (ipdb)
from ipdb import set_trace
set_trace() # Better interface than pdb
# Logging for debugging
import logging
logging.basicConfig(level=logging.DEBUG)
logger = logging.getLogger(__name__)
def fetch_user(user_id):
logger.debug(f'Fetching user: {user_id}')
user = db.query(User).get(user_id)
logger.debug(f'Found user: {user}')
return user
# Profile performance
import cProfile
import pstats
cProfile.run('slow_function()', 'profile_stats')
stats = pstats.Stats('profile_stats')
stats.sort_stats('cumulative')
stats.print_stats(10) # Top 10 slowestGo Debugging
// Delve debugger
// Install: go install github.com/go-delve/delve/cmd/dlv@latest
// Run: dlv debug main.go
import (
"fmt"
"runtime"
"runtime/debug"
)
// Print stack trace
func debugStack() {
debug.PrintStack()
}
// Panic recovery with debugging
func processRequest() {
defer func() {
if r := recover(); r != nil {
fmt.Println("Panic:", r)
debug.PrintStack()
}
}()
// ... code that might panic
}
// Memory profiling
import _ "net/http/pprof"
// Visit http://localhost:6060/debug/pprof/
// CPU profiling
import (
"os"
"runtime/pprof"
)
f, _ := os.Create("cpu.prof")
pprof.StartCPUProfile(f)
defer pprof.StopCPUProfile()
// ... code to profileAdvanced Debugging Techniques
Technique 1: Binary Search Debugging
# Git bisect for finding regression
git bisect start
git bisect bad # Current commit is bad
git bisect good v1.0.0 # v1.0.0 was good
# Git checks out middle commit
# Test it, then:
git bisect good # if it works
git bisect bad # if it's broken
# Continue until bug found
git bisect reset # when doneTechnique 2: Differential Debugging
Compare working vs broken:
## What's Different?
| Aspect | Working | Broken |
| ------------ | ----------- | -------------- |
| Environment | Development | Production |
| Node version | 18.16.0 | 18.15.0 |
| Data | Empty DB | 1M records |
| User | Admin | Regular user |
| Browser | Chrome | Safari |
| Time | During day | After midnight |
Hypothesis: Time-based issue? Check timezone handling.Technique 3: Trace Debugging
// Function call tracing
function trace(
target: any,
propertyKey: string,
descriptor: PropertyDescriptor,
) {
const originalMethod = descriptor.value;
descriptor.value = function (...args: any[]) {
console.log(`Calling ${propertyKey} with args:`, args);
const result = originalMethod.apply(this, args);
console.log(`${propertyKey} returned:`, result);
return result;
};
return descriptor;
}
class OrderService {
@trace
calculateTotal(items: Item[]): number {
return items.reduce((sum, item) => sum + item.price, 0);
}
}Technique 4: Memory Leak Detection
// Chrome DevTools Memory Profiler
// 1. Take heap snapshot
// 2. Perform action
// 3. Take another snapshot
// 4. Compare snapshots
// Node.js memory debugging
if (process.memoryUsage().heapUsed > 500 * 1024 * 1024) {
console.warn("High memory usage:", process.memoryUsage());
// Generate heap dump
require("v8").writeHeapSnapshot();
}
// Find memory leaks in tests
let beforeMemory: number;
beforeEach(() => {
beforeMemory = process.memoryUsage().heapUsed;
});
afterEach(() => {
const afterMemory = process.memoryUsage().heapUsed;
const diff = afterMemory - beforeMemory;
if (diff > 10 * 1024 * 1024) {
// 10MB threshold
console.warn(`Possible memory leak: ${diff / 1024 / 1024}MB`);
}
});Debugging Patterns by Issue Type
Pattern 1: Intermittent Bugs
## Strategies for Flaky Bugs
1. **Add extensive logging**
- Log timing information
- Log all state transitions
- Log external interactions
2. **Look for race conditions**
- Concurrent access to shared state
- Async operations completing out of order
- Missing synchronization
3. **Check timing dependencies**
- setTimeout/setInterval
- Promise resolution order
- Animation frame timing
4. **Stress test**
- Run many times
- Vary timing
- Simulate loadPattern 2: Performance Issues
## Performance Debugging
1. **Profile first**
- Don't optimize blindly
- Measure before and after
- Find bottlenecks
2. **Common culprits**
- N+1 queries
- Unnecessary re-renders
- Large data processing
- Synchronous I/O
3. **Tools**
- Browser DevTools Performance tab
- Lighthouse
- Python: cProfile, line_profiler
- Node: clinic.js, 0xPattern 3: Production Bugs
## Production Debugging
1. **Gather evidence**
- Error tracking (Sentry, Bugsnag)
- Application logs
- User reports
- Metrics/monitoring
2. **Reproduce locally**
- Use production data (anonymized)
- Match environment
- Follow exact steps
3. **Safe investigation**
- Don't change production
- Use feature flags
- Add monitoring/logging
- Test fixes in stagingBest Practices
1. Reproduce First: Can't fix what you can't reproduce 2. Isolate the Problem: Remove complexity until minimal case 3. Read Error Messages: They're usually helpful 4. Check Recent Changes: Most bugs are recent 5. Use Version Control: Git bisect, blame, history 6. Take Breaks: Fresh eyes see better 7. Document Findings: Help future you 8. Fix Root Cause: Not just symptoms
Common Debugging Mistakes
- Making Multiple Changes: Change one thing at a time
- Not Reading Error Messages: Read the full stack trace
- Assuming It's Complex: Often it's simple
- Debug Logging in Prod: Remove before shipping
- Not Using Debugger: console.log isn't always best
- Giving Up Too Soon: Persistence pays off
- Not Testing the Fix: Verify it actually works
Quick Debugging Checklist
## When Stuck, Check:
- [ ] Spelling errors (typos in variable names)
- [ ] Case sensitivity (fileName vs filename)
- [ ] Null/undefined values
- [ ] Array index off-by-one
- [ ] Async timing (race conditions)
- [ ] Scope issues (closure, hoisting)
- [ ] Type mismatches
- [ ] Missing dependencies
- [ ] Environment variables
- [ ] File paths (absolute vs relative)
- [ ] Cache issues (clear cache)
- [ ] Stale data (refresh database)Related skills
Forks & variants (1)
Debugging Strategies has 1 known copy in the catalog totaling 39 installs. They canonicalize to this original listing.
- jurgendn - 39 installs
How it compares
Choose debugging-strategies for methodology across stacks; use language-specific debugger skills when you need IDE breakpoint or tooling specifics.
FAQ
What is the first step when debugging any issue?
Reproduce the issue consistently. Always start by confirming you can reliably recreate the problem with exact steps documented, including environment details and conditions.
How do I debug an intermittent bug that happens randomly?
Add extensive logging with timing information, look for race conditions in concurrent code, check async operation ordering, and stress test by running repeatedly. Use error tracking tools like Sentry for patterns.
What is binary search debugging and when should I use it?
Comment out half your code, narrow down the problematic section by testing, and repeat. Use git bisect for regressions to find which commit introduced the bug. Isolate to smallest reproducible case.
Is Debugging Strategies safe to install?
skills.sh reports 3 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.