systematic-debugging

What this skill does

# Systematic Debugging

- Leverage native parallel subagent dispatch and 200k+ context windows where available.


## Quick Cheat Sheet

| Phase | Goal | Minimum Evidence | Key Red Flags |
|------|------|------------------|---------------|
| 1. Root Cause | Reproduce and isolate the failure | Real error output, stable repro or repro notes, and boundary evidence | Proposing a fix before tracing inputs or recent changes |
| 2. Pattern Analysis | Compare the broken path to a working reference | A concrete diff between working and failing behavior | Hand-waving away small differences as irrelevant |
| 3. Hypothesis and Testing | Test one explanation at a time | One explicit hypothesis and one minimal experiment | Bundling multiple fixes into the same attempt |
| 4. Implementation | Fix the confirmed cause and verify it stays fixed | Failing test or repro first, passing verification after | Calling it done without rerunning the evidence path |

## 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.**

## The Iron Law

```
NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST
```


Increment patch on wording/clarity fixes. Increment minor when adding a new verification step, example, or anti-pattern. Major only on breaking changes to core workflow.

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

## When to Use

Use symptom -> action triggers: when one matches, apply this skill and verify with the protocol below.

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 (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 (rushing guarantees rework)
- Manager wants it fixed NOW (systematic is faster than thrashing)

## 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
   ```

   **Example (multi-layer system):**
   ```bash
   # Layer 1: Workflow
   echo "=== Secrets available in workflow: ==="
   echo "IDENTITY: ${IDENTITY:+SET}${IDENTITY:-UNSET}"

   # Layer 2: Build script
   echo "=== Env vars in build script: ==="
   env | grep IDENTITY || echo "IDENTITY not in environment"

   # Layer 3: Signing script
   echo "=== Keychain state: ==="
   security list-keychains
   security find-identity -v

   # Layer 4: Actual signing
   codesign --sign "$IDENTITY" --verbose=4 "$APP"
   ```

   **This reveals:** Which layer fails (secrets → workflow ✓, workflow → build ✗)

5. **Trace Data Flow**

   **WHEN error is deep in call stack:**

   See `root-cause-tracing.md` in 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

#### What counts as sufficient evidence

Before moving out of Phase 1, you should be able to answer all of these with artifacts instead of intuition:

- What exact input, event, or environment state triggers the failure?
- Where is the first boundary that proves the system diverges from the expected path?
- Which logs, traces, screenshots, or command outputs show the break clearly enough that another engineer could follow them?
- What recent change, dependency drift, config difference, or data condition still remains plausible after you gathered the evidence?

If you cannot point to concrete evidence for those questions yet, you are still investigating and should not be proposing fixes.

### 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 `superpowers:test-driven-development` 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 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 f