Systematic Debugging

Random fixes waste time and create new bugs. Quick patches mask underlying issues.

Core principle: ALWAYS find root cause before attempting fixes.

Usage

/debug

Invoke this skill when encountering any bug, test failure, or unexpected behavior. Follow the four phases in order.

When to use

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

Use this 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

The Iron Law

NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST

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

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
   • What changed that could cause this?
   • Git diff, recent commits
   • New dependencies, config changes
4. Gather Evidence in Multi-Component Systems
   • Log what data enters each component boundary
   • Log what data exits each component boundary
   • Verify environment/config propagation
   • Run once to gather evidence showing WHERE it breaks
   • THEN investigate that specific component
5. Trace Data Flow
   • Where does the bad value originate?
   • What called this with the 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 the same codebase
2. Compare Against References — read reference implementations COMPLETELY, don't skim
3. Identify Differences — list every difference between working and broken, however small
4. Understand Dependencies — what components, settings, environment does it need?

Phase 3: Hypothesis and Testing

1. Form Single Hypothesis — "I think X is the root cause because Y"
2. Test Minimally — smallest possible change, one variable at a time
3. Verify — did it work? Yes = Phase 4. No = new hypothesis. DON'T stack fixes.

Phase 4: Implementation

1. Create Failing Test Case — simplest possible reproduction, automated if possible. Use /tdd for proper failing tests.
2. Implement Single Fix — address the root cause, ONE change at a time, no "while I'm here" improvements.
3. Verify Fix — test passes? No other tests broken? Issue actually resolved? Use /verify before claiming done.

If fix doesn't work:

• If < 3 attempts: return to Phase 1, re-analyze with new information
• If >= 3 attempts: STOP and question the architecture

3+ failed fixes indicate an architectural problem:

• Each fix reveals new coupling in different places
• Fixes require massive refactoring
• Each fix creates new symptoms elsewhere
• Discuss with the user before attempting more fixes

Red Flags - STOP and Follow Process

• "Quick fix for now, investigate later"
• "Just try changing X and see if it works"
• "Add multiple changes, run tests"
• "It's probably X, let me fix that"
• "I don't fully understand but this might work"
• Proposing solutions before tracing data flow
• "One more fix attempt" (when already tried 2+)

ALL of these mean: STOP. Return to Phase 1.

Common Rationalizations

Quick Reference

Related Skills

• /tdd — TDD cycle for creating failing test cases in Phase 4
• /verify — verification before claiming the fix is complete