Systematic Debug

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.

Replaces: superpowers:systematic-debugging Delegates to: OMC debugger agent (stack trace analysis, root cause isolation)

The Iron Law

NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST

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

When to Use

Use for ANY technical issue:

• Test failures
• Production bugs
• 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
• You don't fully understand the issue

The Four Phases

You MUST 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, environmental differences

4. Gather Evidence in Multi-Component Systems

   Copy

   For EACH component boundary:
     - Log what data enters the component
     - Log what data exits the component
     - Verify environment/config propagation
     - Check state at each layer
   
   Run once to gather evidence showing WHERE it breaks
   → Identify the failing component
   → Investigate that specific component
   

5. Trace Data Flow

   • Where does the bad value originate?
   • What called this with the bad value?
   • Keep tracing upstream 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
   • What works that's similar to what's broken?

2. Compare Against References

   • If implementing a pattern, 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
   • Don't assume "that can't matter"

4. Understand Dependencies

   • What other components does this need?
   • What settings, config, environment?
   • What assumptions does it make?

Phase 3: Hypothesis and Testing

1. Form Single Hypothesis

   • State clearly: "I think X is the root cause because Y"
   • Write it down — be specific, not vague

2. Test Minimally

   • Make the SMALLEST possible change to test hypothesis
   • 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
   • Automated test if possible
   • MUST exist before fixing

2. Implement Single Fix

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

3. Verify Fix

   • Test passes now?
   • No other tests broken?
   • Issue actually resolved?

4. 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

5. If 3+ Fixes Failed: Question Architecture

   Signals of an architectural problem:

   • Each fix reveals new shared state / coupling / problems in different places
   • 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 user before attempting more fixes.

   This is NOT a failed hypothesis — this is a wrong architecture.

OMC debugger Agent Delegation

Use the OMC debugger agent during Phases 1–3:

• Stack trace analysis
• Root cause isolation
• Regression isolation
• Build/compilation error resolution

But: Do NOT blindly trust agent results. Verify the reported cause independently.

Rationalization Prevention

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"
• "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"
• 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).

Quick Reference

Integration

Entry point: Triggered by any bug, test failure, or unexpected behavior during work Exit point: Fix verified → continue with verify-completion

OMC delegation:

• debugger agent: root cause analysis, stack trace analysis
• test-engineer agent: failing test case creation (Phase 4)
• ultraqa: post-fix verification cycle