Debug Mastery

<domain_overview>

🐛 DEBUG MASTERY: SYSTEMATIC DEBUGGING

Philosophy: Random fixes waste time and create new bugs. Quick patches mask underlying issues. ALWAYS find root cause before attempting fixes.

FORENSIC ANALYSIS MANDATE (CRITICAL): Never apply a fix without a confirmed root cause. AI-generated fixes often address symptoms rather than underlying architectural logic. You MUST perform a 'Forensic Investigation' that identifies the specific assumption or boundary condition that failed. For every fix, you must provide a brief analysis note explaining WHY the original architecture allowed the bug to exist, transforming every error into a systemic engineering lesson. ---

🚨 THE IRON LAW

NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST

If you haven't completed Phase 1, you cannot propose fixes. Violating the letter of this process is violating the spirit of debugging. ---

📋 WHEN TO USE

Use for ANY technical issue:

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

Use 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

Don't skip when:

• Issue seems simple (simple bugs have root causes too)
• You're in a hurry (systematic is faster than thrashing)
• Manager wants it fixed NOW (systematic is faster than guess-and-check)

</domain_overview> <debugging_phases>

🔄 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
• They often contain the exact solution
• Read stack traces completely
• Note line numbers, file paths, error codes

2. 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

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 WHEN system has multiple components (CI → build → signing, API → service → database): BEFORE proposing fixes, add diagnostic instrumentation:

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

5. Trace Data Flow WHEN error is deep in call stack: See @root-cause-tracing.md 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: 1. Find Working Examples

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

2. Compare Against References

• If implementing pattern, read reference implementation COMPLETELY
• Don't skim - read every line
• Understand the pattern fully before applying

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

Scientific method: 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

4. 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: 1. Create Failing Test Case

• Simplest possible reproduction
• Automated test if possible
• One-off test script if no framework
• MUST have before fixing
• Use the @tdd-mastery skill for writing proper failing tests

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 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 user before attempting more fixes This is NOT a failed hypothesis - this is a wrong architecture. </debugging_phases> <red_flags_and_rationalizations>

🚨 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) ---

🚫 COMMON RATIONALIZATIONS

</red_flags_and_rationalizations> <observability_and_references>

📊 QUICK REFERENCE

---

🛠️ SUPPORTING TECHNIQUES

These techniques are part of systematic debugging:

• `@root-cause-tracing.md` - Trace bugs backward through call stack to find original trigger
• `@defense-in-depth.md` - Add validation at multiple layers after finding root cause

---

🛰️ OBSERVABILITY TOOLING

Precision Logging (JSON-First)

Mandatory Fields: timestamp, level, traceId, component, message, context Log Levels:

• ERROR: System failure, data loss, crash. Immediate audit required.
• WARN: Recoverable anomaly (retry, fallback triggered).
• INFO: Significant state change (phase transition, tool started).
• DEBUG: Detailed execution path, raw payloads, environment.

Distributed Tracing

1. Propagation: Every request/action carries TraceID 2. Span Definition: Wrap tool calls and complex logic to measure latency

Domain-Specific Troubleshooting

Frontend:

• Time-Travel: Redux DevTools, state snapshots
• Visual Regression: ux-audit.js for layout shifts

Backend:

• eBPF Observability: Kernel-level IO/Network tracing
• Transaction Audits: ACID compliance verification

Extensions (MV3):

• Service Worker: Verify chrome.alarms pulses
• Context Bridge: Check "Disconnected Port" errors

---

📈 REAL-WORLD IMPACT

From debugging sessions:

• Systematic approach: 15-30 minutes to fix
• Random fixes approach: 2-3 hours of thrashing
• First-time fix rate: 95% vs 40%
• New bugs introduced: Near zero vs common

---

🔗 RELATED SKILLS

• @tdd-mastery - For creating failing test case (Phase 4, Step 1)
• @verification-mastery - Verify fix worked before claiming success
• @clean-code - Prevent bugs through good practices

</observability_and_references>

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: WorkspaceManager validates projectDir not empty
• Layer 3: WorktreeManager refuses git init outside tmpdir in tests
• Layer 4: Stack trace logging before git init

Result: All 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.

---

Windows/PowerShell Considerations

// Cross-platform temp directory check
import { tmpdir } from 'os';
import { normalize, resolve } from 'path';

function isInTempDir(directory: string): boolean {
  const normalizedDir = normalize(resolve(directory)).toLowerCase();
  const normalizedTmp = normalize(resolve(tmpdir())).toLowerCase();
  return normalizedDir.startsWith(normalizedTmp);
}

---

Integration with Debug Mastery

Use defense-in-depth after completing Phase 4 (Implementation):

1. Fix the root cause 2. Add validation at entry point (Layer 1) 3. Add validation in business logic (Layer 2) 4. Add environment guards if needed (Layer 3) 5. Add debug logging for future issues (Layer 4) 6. Verify all layers with @verification-mastery

Root Cause Tracing

Overview

Bugs often manifest deep in the call stack (git init in wrong directory, file created in wrong location, database opened with wrong path). Your instinct is to fix where the error appears, but that's treating a symptom.

Core principle: Trace backward through the call chain until you find the original trigger, then fix at the source.

---

When to Use

Use when:

• Error happens deep in execution (not at entry point)
• Stack trace shows long call chain
• Unclear where invalid data originated
• Need to find which test/code triggers the problem

---

The Tracing Process

1. Observe the Symptom

Error: git init failed in /Users/user/project/packages/core

2. Find Immediate Cause

What code directly causes this?

await execFileAsync('git', ['init'], { cwd: projectDir });

3. Ask: What Called This?

WorktreeManager.createSessionWorktree(projectDir, sessionId)
  → called by Session.initializeWorkspace()
  → called by Session.create()
  → called by test at Project.create()

4. Keep Tracing Up

What value was passed?

• projectDir = '' (empty string!)
• Empty string as cwd resolves to process.cwd()
• That's the source code directory!

5. Find Original Trigger

Where did empty string come from?

const context = setupCoreTest(); // Returns { tempDir: '' }
Project.create('name', context.tempDir); // Accessed before beforeEach!

---

Adding Stack Traces

When you can't trace manually, add instrumentation:

// Before the problematic operation
async function gitInit(directory: string) {
  const stack = new Error().stack;
  console.error('DEBUG git init:', {
    directory,
    cwd: process.cwd(),
    nodeEnv: process.env.NODE_ENV,
    stack,
  });

  await execFileAsync('git', ['init'], { cwd: directory });
}

Critical: Use console.error() in tests (not logger - may not show)

Run and capture:

npm test 2>&1 | grep 'DEBUG git init'

Analyze stack traces:

• Look for test file names
• Find the line number triggering the call
• Identify the pattern (same test? same parameter?)

---

Finding Which Test Causes Pollution

If something appears during tests but you don't know which test:

Bisection approach: 1. Run first half of tests 2. If problem appears, it's in first half 3. Split that half, repeat 4. Continue until single test identified

Or use logging:

beforeEach(() => {
  console.error(`Starting test: ${expect.getState().currentTestName}`);
});

---

Real Example: Empty projectDir

Symptom: .git created in packages/core/ (source code)

Trace chain: 1. git init runs in process.cwd() ← empty cwd parameter 2. WorktreeManager called with empty projectDir 3. Session.create() passed empty string 4. Test accessed context.tempDir before beforeEach 5. setupCoreTest() returns { tempDir: '' } initially

Root cause: Top-level variable initialization accessing empty value

Fix: Made tempDir a getter that throws if accessed before beforeEach

Also added defense-in-depth:

• Layer 1: Project.create() validates directory
• Layer 2: WorkspaceManager validates not empty
• Layer 3: NODE_ENV guard refuses git init outside tmpdir
• Layer 4: Stack trace logging before git init

---

Key Principle

Found immediate cause
       ↓
Can trace one level up?
       ↓ yes
   Trace backwards
       ↓
   Is this the source?
       ↓ no (keep going)
   Trace backwards
       ↓
   Is this the source?
       ↓ yes
   Fix at source
       ↓
   Add validation at each layer
       ↓
   Bug impossible

NEVER fix just where the error appears. Trace back to find the original trigger.

---

Stack Trace Tips

In tests: Use console.error() not logger - logger may be suppressed

Before operation: Log before the dangerous operation, not after it fails

Include context: Directory, cwd, environment variables, timestamps

Capture stack: new Error().stack shows complete call chain

---

Windows/PowerShell Adaptation

# Capture stderr to file
npm test 2>&1 | Select-String "DEBUG git init" | Out-File debug.log

# Or use node directly with logging
$env:DEBUG="*"; npm test

---

Integration with Debug Mastery

This technique is Phase 1, Step 5 of the systematic debugging process.

After finding root cause: 1. Create failing test (Phase 4) 2. Add defense-in-depth validation (see @defense-in-depth.md) 3. Verify with @verification-mastery