systematic-debugging

name

systematic-debugging

description

Systematic 4-phase debugging process with Iron Law: Root Cause Investigation → Pattern Analysis → Hypothesis & Testing → Implementation. Use when encountering any bug, test failure, unexpected behavior, or build failure — BEFORE proposing fixes. Auto-trigger: load when /coder VERIFY fails 3x consecutively. Keywords: bug, test failing, stuck, not working, can't fix, root cause, 3x fail, test loop, flaky test, unexpected behavior, debugging, investigate. Do NOT use for pre-implementation planning (that is /planner territory).

Systematic Debugging

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 (including 3x fail loop in /coder VERIFY)
• 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)
• 3x test fails — this is the MOST important time to use this skill

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
   • Read stack traces completely
   • Note line numbers, file paths, error codes
   • Run: go test -v -run TestXxx ./... to see full output

2. Reproduce Consistently

   • Can you trigger it reliably?
   • What are the exact steps?
   • go test -count=1 -run TestXxx ./... (disables cache, ensures fresh run)
   • If not reproducible → gather more data, don't guess

3. Check Recent Changes

   • What changed that could cause this?
   • git diff HEAD~1, recent commits
   • New dependencies, config changes
   • Environmental differences

4. Gather Evidence in Multi-Component Systems

   WHEN system has multiple components (handler → service → repository):

   BEFORE proposing fixes, add diagnostic instrumentation:

   For EACH component boundary:
     - Log what data enters component
     - Log what data exits component
     - Verify context/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 (Go multi-layer diagnostic):

   // Layer 1: Handler
   func (h *UserHandler) GetUser(w http.ResponseWriter, r *http.Request) {
       id := chi.URLParam(r, "id")
       slog.Debug("handler.GetUser", "id", id)
   
       // Layer 2: Service
       user, err := h.svc.GetUser(r.Context(), id)
       slog.Debug("service.GetUser result", "id", id, "err", err)
   }
   
   // Layer 3: Repository (add temporarily in Find method)
   // slog.Debug("repo.Find called", "id", id, "stack", string(debug.Stack()))
   

   This reveals: Which layer receives invalid data

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
   • grep -r "func.*GetUser" ./internal/ to find similar functions

2. Compare Against References

   • 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
   • go test -v -run TestXxx -count=1 ./...
   • 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
   • go test -v -run TestXxx -count=1 ./... must FAIL before fix
   • Use tdd-rules skill for proper failing test creation (loads tdd-shapes/.md per cascade)
   • For concurrency bugs: go test -race -run TestXxx ./...

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

   • go test -v -run TestXxx -count=1 ./... passes?
   • go test ./... — 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 major 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

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"
• "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 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

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 (use tdd-rules skill).
"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.
"go test is slow, I'll skip verification"	Unverified fixes are not fixes. Run go test -count=1 -run TestXxx ./....

Integration with /coder VERIFY Phase

Auto-trigger: Load this skill when tests fail 3x consecutively in /coder VERIFY.

Entry point: Start at Phase 1 with the failing go test -v ./... output as evidence.

Exit: Once root cause found and single fix applied, return to VERIFY: go vet ./... && make fmt && make lint && make test

If investigation reveals architectural issue → escalate to user (do NOT attempt Fix #4).

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

Supporting Techniques

• 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 time.Sleep with condition polling

Related skills:

• tdd-rules — For creating failing test case (Phase 4, Step 1; per-language idioms in tdd-shapes/.md)