systematic-debugging
Use on any bug, test failure, or unexpected behavior, before fixes.
SKILL.md.claude/skills/systematic-debugging/SKILL.md
GitHubSystematic Debugging
Overview
Random fixes waste time and create new bugs. Quick patches mask underlying issues.
Core principle: ALWAYS find root cause before attempting fixes. Symptom fixes are failure.
Violating the letter of this process is violating the spirit of debugging.
Iron Law: No fixes without root-cause investigation first. If Phase 1 isn't complete, don't propose fixes.
When to Use
Use for ANY technical issue:
- Test failures
- Bugs in production
- Unexpected behavior
- Performance problems
- Build failures
- Integration issues
Use this ESPECIALLY when:
- Under time pressure or "just one quick fix" seems obvious — rushing guarantees rework
- You've already tried multiple fixes, or the previous fix didn't work
- The issue seems simple — simple bugs still have root causes
The Four Phases
You MUST complete each phase before proceeding to the next.
Phase 1: Root Cause Investigation
BEFORE attempting ANY fix:
Read Error Messages Carefully
- Don't skip past errors or warnings
- They often contain the exact solution
- Read stack traces completely
- Note line numbers, file paths, error codes
Reproduce Consistently
- Can you trigger it reliably?
- What are the exact steps?
- Does it happen every time?
- If not reproducible → gather more data, don't guess
Check Recent Changes
- What changed that could cause this?
- Git diff, recent commits
- New dependencies, config changes
- Environmental differences
Trace Data Flow
WHEN error is deep in call stack:
See
root-cause-tracing.mdin this directory for the complete backward tracing technique.Quick version:
- Where does bad value originate?
- What called this with bad value?
- Keep tracing up until you find the source
- Fix at source, not at symptom
Phase 2: Pattern Analysis
Find the pattern before fixing:
Find Working Examples
- Locate similar working code in same codebase — when it's unfamiliar or the search spans many files, dispatch a Haiku
Exploreto find them (pure location); compare inline - What works that's similar to what's broken?
- Locate similar working code in same codebase — when it's unfamiliar or the search spans many files, dispatch a Haiku
Compare Against References
- If implementing pattern, read reference implementation COMPLETELY
- Don't skim - read every line
- Understand the pattern fully before applying
Identify Differences
- What's different between working and broken?
- List every difference, however small
- Don't assume "that can't matter"
Understand Dependencies
- What other components does this need?
- What settings, config, environment?
- What assumptions does it make?
Phase 3: Hypothesis and Testing
Scientific method:
Form Single Hypothesis
- State clearly: "I think X is the root cause because Y"
- Write it down
- Be specific, not vague
Test Minimally
- Make the SMALLEST possible change to test hypothesis
- One variable at a time
- Don't fix multiple things at once
Verify Before Continuing
- Did it work? Yes → Phase 4
- Didn't work? Form NEW hypothesis
- DON'T add more fixes on top
When You Don't Know
- Say "I don't understand X"
- Don't pretend to know
- Ask for help
- Research more
Phase 4: Implementation
Fix the root cause, not the symptom:
Create Failing Test Case
- Simplest possible reproduction
- Automated test if possible
- One-off test script if no framework
- MUST have before fixing
- Use the
superpowers:test-driven-developmentskill for writing proper failing tests
Implement Single Fix
- Address the root cause identified
- ONE change at a time
- No "while I'm here" improvements
- No bundled refactoring
Verify Fix
- Test passes now?
- No other tests broken?
- Issue actually resolved?
If Fix Doesn't Work
- STOP
- Count: How many fixes have you tried?
- If < 3: Return to Phase 1, re-analyze with new information
- If ≥ 3: STOP and question the architecture (step 5 below)
- DON'T attempt Fix #4 without architectural discussion
If 3+ Fixes Failed: Question Architecture
Pattern indicating architectural problem:
- Each fix reveals new shared state/coupling/problem in different place
- Fixes require "massive refactoring" to implement
- Each fix creates new symptoms elsewhere
STOP and question fundamentals:
- Is this pattern fundamentally sound?
- Are we "sticking with it through sheer inertia"?
- Should we refactor architecture vs. continue fixing symptoms?
Discuss with your human partner before attempting more fixes
This is NOT a failed hypothesis - this is a wrong architecture.
Red Flags - STOP and Follow Process
If you catch yourself thinking:
- "Quick fix for now, investigate later"
- "Just try changing X and see if it works"
- "Add multiple changes, run tests"
- "Skip the test, I'll manually verify"
- "It's probably X, let me fix that"
- "I don't fully understand but this might work"
- "Pattern says X but I'll adapt it differently"
- "Here are the main problems: [lists fixes without investigation]"
- Proposing solutions before tracing data flow
- "One more fix attempt" (when already tried 2+)
- Each fix reveals new problem in different place
ALL of these mean: STOP. Return to Phase 1.
If 3+ fixes failed: Question the architecture (see Phase 4.5)
your human partner's Signals You're Doing It Wrong
Watch for these redirections:
- "Is that not happening?" - You assumed without verifying
- "Will it show us...?" - You should have added evidence gathering
- "Stop guessing" - You're proposing fixes without understanding
- "Ultrathink this" - Question fundamentals, not just symptoms
- "We're stuck?" (frustrated) - Your approach isn't working
When you see these: STOP. Return to Phase 1.
Common Rationalizations
See ~/.claude/references/anti-patterns-common-rationalizations.md
When Process Reveals "No Root Cause"
If systematic investigation reveals issue is truly environmental, timing-dependent, or external:
- You've completed the process
- Document what you investigated
- Implement appropriate handling (retry, timeout, error message)
- Add monitoring/logging for future investigation
But: 95% of "no root cause" cases are incomplete investigation.