superpowers-systematic-debugging

name	superpowers-systematic-debugging
description	Any bug, failing or flaky test, or surprise behavior? Load BEFORE you investigate or guess.

Systematic Debugging

Overview

Random fixes waste time, create new bugs. Quick patches mask real issue.

Core principle: ALWAYS find root cause before fixes. Symptom fixes = failure.

Break letter of process = break spirit of debugging.

The Iron Law

NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST

Phase 1 not done? Cannot propose fixes.

When to Use

ANY technical issue: test failures, production bugs, unexpected behavior, performance problems, build failures, integration issues.

ESPECIALLY when:

• Under time pressure (emergencies make guessing tempting)
• "Just one quick fix" seems obvious
• Already tried multiple fixes
• Previous fix didn't work
• Don't fully understand the issue

Don't skip when:

• Issue seems simple (simple bugs have root causes too)
• In a hurry (rushing guarantees rework)
• Manager wants it NOW (systematic beats thrashing)

The Four Phases

You MUST complete each phase before the next.

Phase 1: Root Cause Investigation

BEFORE attempting ANY fix:

1. Read Error Messages Carefully

   • Don't skip errors or warnings — often contain the exact solution
   • Read stack traces completely; note line numbers, file paths, error codes

2. Reproduce Consistently

   • Trigger it reliably? Exact steps?
   • Not reproducible → gather more data, don't guess

3. Check Recent Changes

   • What changed that could cause this? (git diff, recent commits, new deps, config)

4. Gather Evidence in Multi-Component Systems

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

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

   Example (multi-layer system):

   echo "=== Secrets available in workflow ==="
   echo "IDENTITY: ${IDENTITY:+SET}${IDENTITY:-UNSET}"
   echo "=== Env vars in build script ==="
   env | grep IDENTITY || echo "IDENTITY not in environment"
   echo "=== Keychain state ==="
   security find-identity -v
   

   This reveals which layer fails (secrets → workflow ✓, workflow → build ✗).

5. Trace Data Flow

   WHEN error deep in call stack: see Root Cause Tracing reference (auto-included below) for complete backward-tracing technique.

   Quick version: Where does bad value originate? What called this with bad value? Trace up until you find source. Fix at source, not symptom.

Phase 2: Pattern Analysis

1. Find Working Examples — locate similar working code in same codebase
2. Compare Against References — implementing a pattern? Read reference implementation COMPLETELY (every line, no skimming)
3. Identify Differences — list every difference between working and broken, however small. Don't assume "that can't matter"
4. Understand Dependencies — what components, settings, config, environment, assumptions does this need?

Phase 3: Hypothesis and Testing

1. Form Single Hypothesis — "I think X is root cause because Y." Write it down. Be specific.
2. Test Minimally — SMALLEST possible change to test it. One variable at a time.
3. Verify Before Continuing — Worked? → Phase 4. Didn't? → form NEW hypothesis. DON'T pile fixes on top.
4. When You Don't Know — say "I don't understand X." Don't pretend. Ask for help. Research more.

Phase 4: Implementation

Fix root cause, not symptom:

1. Create Failing Test Case — simplest reproduction, automated if possible. MUST have before fixing. Use superpowers-test-driven-development skill.
2. Implement Single Fix — address root cause. ONE change. No "while I'm here" improvements, no bundled refactoring.
3. Verify Fix — test passes now? No other tests broken? Issue actually resolved? (Use superpowers-verification-before-completion skill.)
4. If Fix Doesn't Work — STOP. Count fixes tried. < 3: return to Phase 1 with new info. ≥ 3: STOP and question architecture (step 5). DON'T attempt fix #4 without architectural discussion.
5. If 3+ Fixes Failed: Question Architecture
   • Pattern: each fix reveals new coupling elsewhere; fixes require "massive refactoring"; each fix creates new symptoms.
   • STOP. Question fundamentals: Is this pattern sound? Continuing through inertia? Refactor vs. keep patching symptoms?
   • Discuss with your human partner before more fixes. NOT a failed hypothesis — a wrong architecture.

Red Flags - STOP and Follow Process

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"
• "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 a new problem in a different place

ALL of these mean: STOP. Return to Phase 1. 3+ fixes failed: question architecture (Phase 4.5).

Signals You're Doing It Wrong

Watch for these redirections from your human partner:

• "Is that not happening?" — you assumed without verifying
• "Will it show us...?" — you should have added evidence gathering
• "Stop guessing" — you're proposing fixes without understanding
• "We're stuck?" (frustrated) — your approach isn't working

See these: STOP. Return to Phase 1.

Common Rationalizations

Excuse	Reality
"Issue is simple, don't need process"	Simple issues have root causes too. Process is fast for simple bugs.
"Emergency, no time for process"	Systematic debugging is FASTER than guess-and-check thrashing.
"Just try this first, then investigate"	First fix sets the pattern. Do it right from the start.
"I'll write test after confirming fix works"	Untested fixes don't stick. Test first proves it.
"Multiple fixes at once saves time"	Can't isolate what worked. Causes new bugs.
"Reference too long, I'll adapt the pattern"	Partial understanding guarantees bugs. Read it completely.
"I see the problem, let me fix it"	Seeing symptoms ≠ understanding root cause.
"One more fix attempt" (after 2+ failures)	3+ failures = architectural problem. Question pattern, don't fix again.

Quick Reference

Phase	Key Activities	Success Criteria
1. Root Cause	Read errors, reproduce, check changes, gather evidence	Understand WHAT and WHY
2. Pattern	Find working examples, compare	Identify differences
3. Hypothesis	Form theory, test minimally	Confirmed or new hypothesis
4. Implementation	Create test, fix, verify	Bug resolved, tests pass

When Process Reveals "No Root Cause"

Systematic investigation shows issue is truly environmental, timing-dependent, or external? Process complete. Document what you investigated, implement appropriate handling (retry, timeout, error message), add monitoring/logging.

But: 95% of "no root cause" cases = incomplete investigation.

Supporting Techniques (auto-included references)

• Root Cause Tracing — trace bugs backward through call stack to original trigger
• Defense in Depth — add validation at multiple layers after finding root cause
• Condition-Based Waiting — replace arbitrary timeouts with condition polling

Related skills: superpowers-test-driven-development (Phase 4 failing test) · superpowers-verification-before-completion (confirm the fix).