<!-- Adapted from obra/superpowers systematic-debugging skill (v5.0.7), MIT-licensed, copyright 2025 Jesse Vincent. Modifications copyright 2026 Joe Amditis. v0.3.0 adds a research phase between Phase 1 (Root Cause Investigation) and Phase 2 (Pattern Analysis) per the v0.2.0 architecture's research-at-entry-point rule (debugging is an entry-point stage, the work begins from a bug report, not an upstream artifact). See CREDITS.md. -->

Systematic Debugging

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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

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

When to Use

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

Move through the phases in order. Phase 1 is mandatory; if it produces a clear root cause and a confident fix, you may go directly to Phase 4 (Implementation). Otherwise complete Phase 2 (Pattern Analysis) and Phase 3 (Hypotheses) in order before Phase 4. Between Phase 1 and Phase 2, when you've decided pattern analysis is needed, run the research phase (default-on, see below) so pattern analysis has external context to build on.

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):

   # 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

Research phase

After Phase 1 (Root Cause Investigation) and before Phase 2 (Pattern Analysis), gather outside context. Phase 1 produced internal evidence (error messages, repro steps, recent diffs); the research phase adds external information that pattern analysis can build on.

Default-on. Skip only with explicit, justified statement per the skip protocol below.

This phase only fires when entering Phase 2. If Phase 1 yielded the root cause directly and you're going Phase 1 → Phase 4 (Implementation), you don't reach the research phase. The skip protocol governs the case where you've decided pattern analysis is needed but want to skip the research that would inform it.

1. Default research kinds (all four)

Kind	Purpose	Tool
Web	Search the literal error string and the framework/library's open GitHub issues for prior reports	WebSearch + WebFetch (via subagent)
Codebase prior-bugs	git log --grep for related historical fixes; spots regressions and prior work in the same area	Bash + Grep (via subagent)
Authoritative	Fetch current live docs/spec for the API or library involved; catches "am I using this wrong" cases	WebFetch (via subagent)
User-context	Check MEMORY.md for related debugging history	Read (inline, no subagent)

2. Dispatch

Three subagents in parallel (web via general-purpose, codebase prior-bugs via Explore, authoritative via general-purpose) plus the inline memory check running concurrently in the main thread. The subagent prompts each carry the bug context from Phase 1 (error message, repro, current diff) so they don't have to rediscover it.

3. Findings location

Findings land in .superpowers/debug-log-<slug>.md where <slug> is YYYY-MM-DD-<short-bug-description>. Examples:

.superpowers/debug-log-2026-05-05-test-failure-auth-handler.md
.superpowers/debug-log-2026-05-12-build-fails-on-arm64.md
.superpowers/debug-log-2026-06-03-flaky-redis-pubsub.md

The skill creates the file on first invocation if it doesn't exist; subsequent invocations on the same bug append. Each entry includes:

• Date/time of the research run
• Which research kinds fired (or were skipped, with the locked skip-justification line)
• Findings: 3-5 bullets per kind that fired, including load-bearing links/refs
• "Considered but ruled out" notes so future-you knows what was checked

Add .superpowers/ to your project's .gitignore so debug logs don't get accidentally committed. The upstream superpowers plugin uses this convention; superjawn follows the same pattern.

4. Skip protocol

If skipping, write one line to .superpowers/debug-log-<slug>.md: Skipped research because <reason>. <Verifiable pointer if applicable>.

Valid reasons:

• Trivial scope (typo, comment edit, single-line config)
• Fresh prior research, same topic in current session OR within last 7 days with verifiable spec/plan pointer. If the pointer doesn't resolve, the skip is invalid. (Beyond 7 days, repeat the research even if you remember the prior findings, the landscape drifts.)
• User explicit, must quote the phrase that authorized the skip.
• Repeat of identical task, must include a pointer to the prior successful run.

Invalid reasons: "I think I know", "seems straightforward", "moving fast", "user wants this done quickly", "already familiar with this codebase". If those are tempting, do the research.

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. Reproduce the failure

   • Simplest faithful reproduction: an existing test, a focused command, a log, or a new failing test
   • Confirm it fails for the reported reason
   • MUST have before fixing
   • Keep it as a persistent regression test only when the bug is likely to recur or affects an important contract, non-obvious logic, or high-impact behavior

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

   • The same reproduction from Step 1 now passes?
   • 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 fix for now, investigate later"
• "Just try changing X and see if it works"
• "Add multiple changes, run tests"
• "Skip the reproduction, I'll eyeball the fix"
• "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)

your human partner's Signals You're Doing It Wrong

Watch for these redirections:

• "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
• "Ultrathink this" - Question fundamentals, not just symptoms
• "We're stuck?" (frustrated) - Your approach isn't working

When you 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 reproduce it after confirming the fix works"	A fix you never saw fail proves nothing. Reproduce first, then rerun the same evidence.
"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	Reproduce, fix, verify with the same evidence	Bug resolved, reproduction passes

When Process Reveals "No Root Cause"

If systematic investigation reveals issue is truly environmental, timing-dependent, or external:

1. You've completed the process
2. Document what you investigated
3. Implement appropriate handling (retry, timeout, error message)
4. Add monitoring/logging for future investigation

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

Supporting Techniques

These techniques are part of systematic debugging and available in this directory:

• 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
• condition-based-waiting.md - Replace arbitrary timeouts with condition polling

Related skills:

• superjawn:verification-before-completion - Verify fix worked before claiming success

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