systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes

Model	Source	Category
opus	core	Workflow

Tools: Read, Glob, Grep, Bash, Edit, Write, Task

Overview

Random fixes waste time and create new bugs. Quick patches mask underlying issues.

Mandatory Announcement — FIRST OUTPUT before anything else:

┏━ 🔍 systematic-debugging ━━━━━━━━━━━━━━━━━━━━━━┓
┃ [one-line description of what bug/failure]      ┃
┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛

No exceptions. Box frame first, then work.

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

**First action — clear test-failure gate (writte

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 re

Full Reference

Systematic Debugging

Overview

Random fixes waste time and create new bugs. Quick patches mask underlying issues.

Mandatory Announcement — FIRST OUTPUT before anything else:

┏━ 🔍 systematic-debugging ━━━━━━━━━━━━━━━━━━━━━━┓
┃ [one-line description of what bug/failure]      ┃
┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛

No exceptions. Box frame first, then work.

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

First action — clear test-failure gate (written by detect-test-failure.sh):

rm -f "$CLAUDE_PROJECT_DIR/.claude/context/.tests-failing"

This clears the test-failure gate so Edit/Write are unblocked during investigation.

Second action — mark debugging session active:

touch /tmp/.armadillo-debugging-active

This enables the gotcha-capture hook to detect framework-level fixes during debugging.

Violating the letter of this process is violating the spirit of debugging.

Model requirement: Root cause analysis requires deep reasoning. Use Opus 4.6 (claude-opus-4-6).

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)

Quick Path: Test Failures

When the issue is a straightforward test failure (not a mystery bug), use this streamlined path before escalating to the full 4-phase investigation:

Capture full output — run failing test, read FULL error (not just summary)
Read test — understand what it expects, assertions, setup/teardown, mocks
Read code under test — trace execution path for the failing case
Trace imports — check breaking interface changes, mock mismatches, shared state
Classify — CODE BUG | CODE GAP | TEST BUG | ENV

Classification	Action
CODE BUG	Fix the implementation
CODE GAP	Add the missing behavior
TEST BUG	Fix the test assertion
ENV	Fix config/setup

Fix root cause — apply targeted fix based on classification
Re-run and verify — run specific test, then full suite

Max 3 cycles. If still failing after 3 rounds → escalate to full 4-phase investigation below.

Quick Path Anti-Patterns

Never Do This	Do This Instead
Delete a failing test	Fix the root cause
Skip/disable tests	Document why if absolutely necessary
Change assertions to match wrong behavior	Fix the code, not the test
Retry the same fix hoping for different results	Re-classify the failure
Add try/catch to suppress errors	Fix the error source
Brute-force random changes	Follow the 7-step process

The Four Phases

You MUST complete each phase before proceeding to the next.

Phase 1: Root Cause Investigation

BEFORE attempting ANY fix:

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
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
Check Recent Changes
- What changed that could cause this?
- Git diff, recent commits
- New dependencies, config changes
- Environmental differences

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 ✗)

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

Phase 2: Pattern Analysis

Find the pattern before fixing:

Find Working Examples
- Locate similar working code in same codebase
- What works that’s similar to what’s broken?
Compare Against References
- If implementing pattern, read reference implementation COMPLETELY
- Don’t skim - read every line
- Understand the pattern fully before applying
Identify Differences
- What’s different between working and broken?
- List every difference, however small
- Don’t assume “that can’t matter”
Understand Dependencies
- What other components does this need?
- What settings, config, environment?
- What assumptions does it make?

Phase 3: Hypothesis and Testing

Scientific method:

Form Single Hypothesis
- State clearly: “I think X is the root cause because Y”
- Write it down
- Be specific, not vague
Test Minimally
- Make the SMALLEST possible change to test hypothesis
- One variable at a time
- Don’t fix multiple things at once
Verify Before Continuing
- Did it work? Yes → Phase 4
- Didn’t work? Form NEW hypothesis
- DON’T add more fixes on top
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:

Create Failing Test Case
- Simplest possible reproduction
- Automated test if possible
- One-off test script if no framework
- MUST have before fixing
- Use the armadillo:test-driven-development skill for writing proper failing tests
Implement Single Fix
- Address the root cause identified
- ONE change at a time
- No “while I’m here” improvements
- No bundled refactoring
Verify Fix
- Test passes now?
- No other tests broken?
- Issue actually resolved?
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
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 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)

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 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”

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

You’ve completed the process
Document what you investigated
Implement appropriate handling (retry, timeout, error message)
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:

armadillo:test-driven-development - For creating failing test case (Phase 4, Step 1)
armadillo: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