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name: debugging description: Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes. Requires root cause investigation before any fix attempts. Random fixes waste time and create new bugs.

Systematic Debugging

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.

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The Iron Law

CopyNO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST

If you haven't completed Phase 1, you cannot propose fixes.

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When to Use

Any technical issue:

• Test failures
• Bugs in production
• Unexpected behavior
• Performance problems
• Build failures
• Integration issues

Especially when:

• Under time pressure (emergencies make guessing tempting)
• "Just one quick fix" seems obvious
• You've already tried multiple fixes
• Previous fix didn't work

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The Four Phases

Complete each phase before proceeding to the next.

Phase 1: Root Cause Investigation

BEFORE attempting ANY fix:

1. Read Error Messages Carefully

   • Don't skip past errors or warnings
   • Read stack traces completely
   • Note line numbers, file paths, error codes

2. Reproduce Consistently

   • Can you trigger it reliably?
   • What are the exact steps?
   • If not reproducible → gather more data, don't guess

3. Check Recent Changes

   • Git diff, recent commits
   • New dependencies, config changes
   • Environmental differences

4. Gather Evidence in Multi-Component Systems

   CopyFor EACH component boundary:
     - Log what data enters
     - Log what data exits
     - Verify environment/config propagation
   
   Run once to gather evidence showing WHERE it breaks
   THEN investigate that specific component
   

5. Trace Data Flow

   • 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

1. Find Working Examples

   • Locate similar working code in same codebase
   • What works that's similar to what's broken?

2. Compare Against References

   • Read reference implementation COMPLETELY
   • Don't skim - read every line

3. Identify Differences

   • What's different between working and broken?
   • List every difference, however small

Phase 3: Hypothesis and Testing

1. Form Single Hypothesis

   • "I think X is the root cause because Y"
   • Be specific, not vague

2. Test Minimally

   • Make the SMALLEST possible change
   • One variable at a time
   • Don't fix multiple things at once

3. Verify Before Continuing

   • Did it work? Yes → Phase 4
   • Didn't work? Form NEW hypothesis
   • DON'T add more fixes on top

Phase 4: Implementation

1. Create Failing Test Case

   • Simplest possible reproduction
   • MUST have before fixing

2. Implement Single Fix

   • Address the root cause
   • ONE change at a time
   • No "while I'm here" improvements

3. Verify Fix

   • Test passes now?
   • No other tests broken?

4. If 3+ Fixes Failed: Question Architecture

   Pattern indicating architectural problem:

   • Each fix reveals new problem in different place
   • Fixes require massive refactoring
   • Each fix creates new symptoms elsewhere

   STOP and question fundamentals before attempting more fixes

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Red Flags - STOP and Return to Phase 1

If you catch yourself thinking:

• "Quick fix for now, investigate later"
• "Just try changing X and see if it works"
• "It's probably X, let me fix that"
• "I don't fully understand but this might work"
• "Here are the main problems: [lists fixes without investigation]"
• Proposing solutions before tracing data flow
• "One more fix attempt" (when already tried 2+)

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Common Rationalizations

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Quick Reference

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Real-World Impact