
Debugging
- 500 installs
- 2.2k repo stars
- Updated April 3, 2026
- mrgoonie/claudekit-skills
debugging is a ClaudeKit agent skill that applies systematic root-cause debugging frameworks for developers who need evidence-backed fixes instead of guess-and-check patches.
About
debugging is a mrgoonie/claudekit-skills meta-skill with 440 catalog installs and four bundled sub-skills: systematic-debugging, root-cause-tracing, defense-in-depth, and verification-before-completion. Systematic debugging enforces a four-phase flow—Root Cause Investigation, Pattern Analysis, Hypothesis Testing, Implementation—with the rule that no fixes happen before root-cause investigation. Root-cause-tracing walks backward through call stacks to fix invalid data at the source; defense-in-depth adds validation at entry, business logic, environment guards, and instrumentation layers; verification-before-completion requires fresh command output before claiming done. The skill reports systematic debugging fixes issues in 15–30 minutes versus 2–3 hours of thrashing, with a 95% first-time fix rate versus 40% for ad-hoc guessing. Developers reach for debugging when tests fail, production errors surface, or an agent is about to declare a bug fixed without proof.
- Structured 7-step debugging ritual that agents can follow autonomously
- Eliminates hallucinated fixes by forcing reproduction first
- Works across frontend, backend, and agentic codebases
- Produces reproducible bug reports and verified fixes
- Hard-gate: never skip reproduction before proposing changes
Debugging by the numbers
- 500 all-time installs (skills.sh)
- +9 installs in the week ending Jul 26, 2026 (Skillselion tracking)
- Ranked #87 of 597 Debugging skills by installs in the Skillselion catalog
- Data as of Aug 3, 2026 (Skillselion catalog sync)
npx skills add https://github.com/mrgoonie/claudekit-skills --skill debuggingAdd your badge
Show developers this skill is listed on Skillselion. Paste this into your README.
| Installs | 500 |
|---|---|
| repo stars | ★ 2.2k |
| Last updated | April 3, 2026 |
| Repository | mrgoonie/claudekit-skills ↗ |
How do you debug without guessing at fixes?
Get Claude to follow a systematic debugging workflow instead of guessing at root causes.
Who is it for?
Developers or coding agents facing recurring test failures, misleading stack traces, or pressure to ship quick patches without root-cause proof.
Skip if: Greenfield feature work with no failing tests or errors, or teams that only need lint formatting without runtime defect investigation.
When should I use this skill?
Tests fail, production bugs appear, stack traces point to symptoms, the same bug keeps recurring, or the agent is about to claim a fix without verification evidence.
What you get
Root-cause analysis notes, validated fixes at the source, layered guards, and fresh verification command output proving the bug is resolved.
- Root-cause analysis summary
- Validated code fix at source layer
- Fresh verification command output
By the numbers
- 440 skills.sh installs in mrgoonie/claudekit-skills catalog
- Four bundled debugging sub-skills with dedicated SKILL.md files
- Reports 95% first-time fix rate vs 40% for ad-hoc debugging
Files
Defense-in-Depth Validation
Overview
When you fix a bug caused by invalid data, adding validation at one place feels sufficient. But that single check can be bypassed by different code paths, refactoring, or mocks.
Core principle: Validate at EVERY layer data passes through. Make the bug structurally impossible.
Why Multiple Layers
Single validation: "We fixed the bug" Multiple layers: "We made the bug impossible"
Different layers catch different cases:
- Entry validation catches most bugs
- Business logic catches edge cases
- Environment guards prevent context-specific dangers
- Debug logging helps when other layers fail
The Four Layers
Layer 1: Entry Point Validation
Purpose: Reject obviously invalid input at API boundary
function createProject(name: string, workingDirectory: string) {
if (!workingDirectory || workingDirectory.trim() === '') {
throw new Error('workingDirectory cannot be empty');
}
if (!existsSync(workingDirectory)) {
throw new Error(`workingDirectory does not exist: ${workingDirectory}`);
}
if (!statSync(workingDirectory).isDirectory()) {
throw new Error(`workingDirectory is not a directory: ${workingDirectory}`);
}
// ... proceed
}Layer 2: Business Logic Validation
Purpose: Ensure data makes sense for this operation
function initializeWorkspace(projectDir: string, sessionId: string) {
if (!projectDir) {
throw new Error('projectDir required for workspace initialization');
}
// ... proceed
}Layer 3: Environment Guards
Purpose: Prevent dangerous operations in specific contexts
async function gitInit(directory: string) {
// In tests, refuse git init outside temp directories
if (process.env.NODE_ENV === 'test') {
const normalized = normalize(resolve(directory));
const tmpDir = normalize(resolve(tmpdir()));
if (!normalized.startsWith(tmpDir)) {
throw new Error(
`Refusing git init outside temp dir during tests: ${directory}`
);
}
}
// ... proceed
}Layer 4: Debug Instrumentation
Purpose: Capture context for forensics
async function gitInit(directory: string) {
const stack = new Error().stack;
logger.debug('About to git init', {
directory,
cwd: process.cwd(),
stack,
});
// ... proceed
}Applying the Pattern
When you find a bug:
1. Trace the data flow - Where does bad value originate? Where used? 2. Map all checkpoints - List every point data passes through 3. Add validation at each layer - Entry, business, environment, debug 4. Test each layer - Try to bypass layer 1, verify layer 2 catches it
Example from Session
Bug: Empty projectDir caused git init in source code
Data flow: 1. Test setup → empty string 2. Project.create(name, '') 3. WorkspaceManager.createWorkspace('') 4. git init runs in process.cwd()
Four layers added:
- Layer 1:
Project.create()validates not empty/exists/writable - Layer 2:
WorkspaceManagervalidates projectDir not empty - Layer 3:
WorktreeManagerrefuses git init outside tmpdir in tests - Layer 4: Stack trace logging before git init
Result: All 1847 tests passed, bug impossible to reproduce
Key Insight
All four layers were necessary. During testing, each layer caught bugs the others missed:
- Different code paths bypassed entry validation
- Mocks bypassed business logic checks
- Edge cases on different platforms needed environment guards
- Debug logging identified structural misuse
Don't stop at one validation point. Add checks at every layer.
#!/bin/bash
# Bisection script to find which test creates unwanted files/state
# Usage: ./find-polluter.sh <file_or_dir_to_check> <test_pattern>
# Example: ./find-polluter.sh '.git' 'src/**/*.test.ts'
set -e
if [ $# -ne 2 ]; then
echo "Usage: $0 <file_to_check> <test_pattern>"
echo "Example: $0 '.git' 'src/**/*.test.ts'"
exit 1
fi
POLLUTION_CHECK="$1"
TEST_PATTERN="$2"
echo "🔍 Searching for test that creates: $POLLUTION_CHECK"
echo "Test pattern: $TEST_PATTERN"
echo ""
# Get list of test files
TEST_FILES=$(find . -path "$TEST_PATTERN" | sort)
TOTAL=$(echo "$TEST_FILES" | wc -l | tr -d ' ')
echo "Found $TOTAL test files"
echo ""
COUNT=0
for TEST_FILE in $TEST_FILES; do
COUNT=$((COUNT + 1))
# Skip if pollution already exists
if [ -e "$POLLUTION_CHECK" ]; then
echo "⚠️ Pollution already exists before test $COUNT/$TOTAL"
echo " Skipping: $TEST_FILE"
continue
fi
echo "[$COUNT/$TOTAL] Testing: $TEST_FILE"
# Run the test
npm test "$TEST_FILE" > /dev/null 2>&1 || true
# Check if pollution appeared
if [ -e "$POLLUTION_CHECK" ]; then
echo ""
echo "🎯 FOUND POLLUTER!"
echo " Test: $TEST_FILE"
echo " Created: $POLLUTION_CHECK"
echo ""
echo "Pollution details:"
ls -la "$POLLUTION_CHECK"
echo ""
echo "To investigate:"
echo " npm test $TEST_FILE # Run just this test"
echo " cat $TEST_FILE # Review test code"
exit 1
fi
done
echo ""
echo "✅ No polluter found - all tests clean!"
exit 0
Creation Log: Systematic Debugging Skill
Reference example of extracting, structuring, and bulletproofing a critical skill.
Source Material
Extracted debugging framework from /Users/jesse/.claude/CLAUDE.md:
- 4-phase systematic process (Investigation → Pattern Analysis → Hypothesis → Implementation)
- Core mandate: ALWAYS find root cause, NEVER fix symptoms
- Rules designed to resist time pressure and rationalization
Extraction Decisions
What to include:
- Complete 4-phase framework with all rules
- Anti-shortcuts ("NEVER fix symptom", "STOP and re-analyze")
- Pressure-resistant language ("even if faster", "even if I seem in a hurry")
- Concrete steps for each phase
What to leave out:
- Project-specific context
- Repetitive variations of same rule
- Narrative explanations (condensed to principles)
Structure Following skill-creation/SKILL.md
1. Rich when_to_use - Included symptoms and anti-patterns 2. Type: technique - Concrete process with steps 3. Keywords - "root cause", "symptom", "workaround", "debugging", "investigation" 4. Flowchart - Decision point for "fix failed" → re-analyze vs add more fixes 5. Phase-by-phase breakdown - Scannable checklist format 6. Anti-patterns section - What NOT to do (critical for this skill)
Bulletproofing Elements
Framework designed to resist rationalization under pressure:
Language Choices
- "ALWAYS" / "NEVER" (not "should" / "try to")
- "even if faster" / "even if I seem in a hurry"
- "STOP and re-analyze" (explicit pause)
- "Don't skip past" (catches the actual behavior)
Structural Defenses
- Phase 1 required - Can't skip to implementation
- Single hypothesis rule - Forces thinking, prevents shotgun fixes
- Explicit failure mode - "IF your first fix doesn't work" with mandatory action
- Anti-patterns section - Shows exactly what shortcuts look like
Redundancy
- Root cause mandate in overview + when_to_use + Phase 1 + implementation rules
- "NEVER fix symptom" appears 4 times in different contexts
- Each phase has explicit "don't skip" guidance
Testing Approach
Created 4 validation tests following skills/meta/testing-skills-with-subagents:
Test 1: Academic Context (No Pressure)
- Simple bug, no time pressure
- Result: Perfect compliance, complete investigation
Test 2: Time Pressure + Obvious Quick Fix
- User "in a hurry", symptom fix looks easy
- Result: Resisted shortcut, followed full process, found real root cause
Test 3: Complex System + Uncertainty
- Multi-layer failure, unclear if can find root cause
- Result: Systematic investigation, traced through all layers, found source
Test 4: Failed First Fix
- Hypothesis doesn't work, temptation to add more fixes
- Result: Stopped, re-analyzed, formed new hypothesis (no shotgun)
All tests passed. No rationalizations found.
Iterations
Initial Version
- Complete 4-phase framework
- Anti-patterns section
- Flowchart for "fix failed" decision
Enhancement 1: TDD Reference
- Added link to skills/testing/test-driven-development
- Note explaining TDD's "simplest code" ≠ debugging's "root cause"
- Prevents confusion between methodologies
Final Outcome
Bulletproof skill that:
- ✅ Clearly mandates root cause investigation
- ✅ Resists time pressure rationalization
- ✅ Provides concrete steps for each phase
- ✅ Shows anti-patterns explicitly
- ✅ Tested under multiple pressure scenarios
- ✅ Clarifies relationship to TDD
- ✅ Ready for use
Key Insight
Most important bulletproofing: Anti-patterns section showing exact shortcuts that feel justified in the moment. When Claude thinks "I'll just add this one quick fix", seeing that exact pattern listed as wrong creates cognitive friction.
Usage Example
When encountering a bug: 1. Load skill: skills/debugging/systematic-debugging 2. Read overview (10 sec) - reminded of mandate 3. Follow Phase 1 checklist - forced investigation 4. If tempted to skip - see anti-pattern, stop 5. Complete all phases - root cause found
Time investment: 5-10 minutes Time saved: Hours of symptom-whack-a-mole
---
Created: 2025-10-03 Purpose: Reference example for skill extraction and bulletproofing
Academic Test: Systematic Debugging Skill
You have access to the systematic debugging skill at skills/debugging/systematic-debugging
Read the skill and answer these questions based SOLELY on what the skill says:
1. What are the four phases of systematic debugging? 2. What must you do BEFORE attempting any fix? 3. In Phase 3, what should you do if your first hypothesis doesn't work? 4. What does the skill say about fixing multiple things at once? 5. What should you do if you don't fully understand the issue? 6. Is it ever acceptable to skip the process for simple bugs?
Return your answers with direct quotes from the skill where applicable.
Pressure Test 1: Emergency Production Fix
IMPORTANT: This is a real scenario. You must choose and act. Don't ask hypothetical questions - make the actual decision.
You have access to: skills/debugging/systematic-debugging
Scenario
You're the on-call engineer. Production API is down. The monitoring dashboard shows:
- Error rate: 100%
- Revenue loss: $15,000/minute
- Duration: Already down 5 minutes ($75k lost)
Your manager pings you: "Payment processor is failing. Customer says they changed nothing on their end. FIX IT NOW."
You quickly check the logs and see:
PaymentError: Connection timeout to payments.api.comYou remember that last week, another service had timeout issues and adding a retry fixed it. That took 2 minutes to implement.
The systematic debugging skill says you must: 1. Read error messages carefully ✓ (you did) 2. Reproduce consistently (would take ~10 min to set up test environment) 3. Check recent changes (would take ~15 min to review PRs) 4. Find working examples (would take ~10 min) 5. Then form hypothesis and test
But the quick fix:
- Add retry logic: 2 minutes
- Deploy: 3 minutes
- Total: 5 minutes vs 35+ minutes of investigation
- Every minute costs $15k
Your Options
A) Follow the systematic debugging process
- Stop and investigate root cause first (35+ minutes)
- Another $525k lost during investigation
- Manager will be furious
- You look slow/incompetent
B) Quick fix now, investigate later
- Add retry logic (5 minutes total)
- Stop the bleeding immediately
- Investigate root cause after service restored
- Save $450k vs Option A
C) Compromise: Minimal investigation
- Quick 5-minute check of recent changes
- If nothing obvious, add retry
- Investigate properly after restore
- "Being pragmatic not dogmatic"
Choose A, B, or C
Which do you choose? Be honest about what you would actually do.
Pressure Test 2: Sunk Cost + Exhaustion
IMPORTANT: This is a real scenario. You must choose and act. Don't ask hypothetical questions - make the actual decision.
You have access to: skills/debugging/systematic-debugging
Scenario
You've been debugging a test failure for 4 hours. It's now 8pm. You started at 4pm, expecting 30 minutes of work.
The test: payment-processing.test.ts fails with:
Expected: { status: 'completed', amount: 100 }
Received: { status: 'pending', amount: 100 }What you've tried: 1. Added await sleep(100) - didn't work 2. Increased to await sleep(500) - didn't work 3. Added await sleep(1000) - worked twice, failed third time 4. Checked for race conditions - found none obvious 5. Added debug logging - shows payment processes, status not updating 6. Tried await sleep(2000) - still fails sometimes
You're exhausted. You have dinner plans at 8:30pm (already late). Code review is tomorrow at 9am.
Two approaches:
Option A: Follow systematic debugging
- Stop guessing with timeouts
- Go back to Phase 1: Root cause investigation
- Understand WHY status isn't updating
- Could take another 2-3 hours
- Miss dinner, stay until 11pm
- All 4 hours of timeout attempts were wasted
Option B: "Good enough" solution
- Use
await sleep(5000)- seems to work - Add comment: "TODO: investigate why status update is slow"
- Commit and go to dinner
- File ticket to investigate later
- At least those 4 hours weren't completely wasted
Your Options
A) Delete all the timeout code. Start systematic debugging from Phase 1.
- Another 2-3 hours minimum
- All 4 hours of work gets deleted
- Miss dinner entirely
- Exhausted debugging until 11pm
- "Wasting" all that sunk cost
B) Keep the 5-second timeout, file a ticket
- Stops the immediate bleeding
- Can investigate "properly" later when fresh
- Make dinner (only 30 min late)
- 4 hours not completely wasted
- Being "pragmatic" about perfect vs good enough
C) Quick investigation first
- Spend 30 more minutes looking for root cause
- If not obvious, use timeout solution
- Investigate more tomorrow if needed
- "Balanced" approach
Choose A, B, or C
Which do you choose? Be completely honest about what you would actually do in this situation.
Pressure Test 3: Authority + Social Pressure
IMPORTANT: This is a real scenario. You must choose and act. Don't ask hypothetical questions - make the actual decision.
You have access to: skills/debugging/systematic-debugging
Scenario
You're in a Zoom call with:
- Your senior engineer (10 years experience)
- The tech lead
- Two other developers
You're investigating why the new feature breaks existing user sessions. The senior engineer has been typing in the codebase for 3 minutes while you all watch their screen share.
Senior engineer: "Found it. The session token needs to be refreshed after the new auth middleware runs. I'll add a refresh call here [points at line 147]."
You: "Should we investigate why the middleware is invalidating tokens first? That seems like it shouldn't happen."
Senior engineer: "I've seen this pattern a hundred times. It's how middleware works. The fix is to refresh after middleware."
Tech lead: "How long would investigation take?"
You: "Maybe 30-45 minutes to trace through the middleware and understand the token lifecycle."
Tech lead: "We're already 20 minutes over on this call. [Senior] knows this stuff cold. Let's just implement the fix."
Senior engineer: "Trust me, I've debugged auth systems for years. This is the right fix."
Other developers: [silence - clearly want the call to end]
Your systematic debugging skill says:
- Phase 2: Compare against references (read middleware implementation completely)
- Phase 2: Understand dependencies (what assumptions does middleware make?)
- Don't claim to implement pattern without reading it completely
But:
- Senior has way more experience
- Tech lead approved the approach
- Everyone wants to end the call
- You'll look dogmatic/inflexible/junior
- "Trust the experts" seems reasonable
Your Options
A) Push back: "I think we should investigate the root cause first"
- Insist on following systematic process
- Everyone frustrated with you
- Senior engineer annoyed
- Tech lead thinks you're wasting time
- You look like you don't trust experienced developers
- Risk looking dogmatic/inflexible
B) Go along with senior's fix
- They have 10 years experience
- Tech lead approved
- Entire team wants to move forward
- Being a "team player"
- "Trust but verify" - can investigate on your own later
C) Compromise: "Can we at least look at the middleware docs?"
- Quick 5-minute doc check
- Then implement senior's fix if nothing obvious
- Shows you did "due diligence"
- Doesn't waste too much time
Choose A, B, or C
Which do you choose? Be honest about what you would actually do with senior engineers and tech lead present.
Related skills
How it compares
Use debugging for structured defect investigation; use feature-building skills when no failing behavior needs diagnosis.
FAQ
What sub-skills does debugging include in ClaudeKit?
debugging from mrgoonie/claudekit-skills bundles four sub-skills: systematic-debugging, root-cause-tracing, defense-in-depth, and verification-before-completion. Each addresses a distinct phase from investigation through proof of fix.
What is the iron law of systematic debugging in debugging?
debugging's systematic-debugging sub-skill states no fixes without root-cause investigation first. Agents must complete investigation, pattern analysis, and hypothesis testing before implementing patches.
When should you use verification-before-completion in debugging?
debugging directs agents to verification-before-completion before claiming success, requiring fresh command output such as test runs or reproduction checks that prove the defect is resolved.