ibanking-api-ai/.agents/skills/systematic-debugging/SKILL.md

name, description, source

name	description	source
systematic-debugging	Four-phase debugging methodology. Always find root cause before attempting fixes.	obra/superpowers (pinned 2026-03-19)

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.

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

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 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.

5. Trace Data Flow

   • 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
2. Compare Against References — Read reference implementation COMPLETELY
3. Identify Differences — List every difference, however small
4. Understand Dependencies — Settings, config, environment, assumptions

Phase 3: Hypothesis and Testing

Scientific method:

1. Form Single Hypothesis — "I think X is the root cause because Y"
2. Test Minimally — Make the SMALLEST possible change to test
3. Verify Before Continuing — Did it work? Yes → Phase 4. No → NEW hypothesis
4. When You Don't Know — Say "I don't understand X". Don't pretend.

Phase 4: Implementation

Fix the root cause, not the symptom:

1. Create Failing Test Case — Simplest possible reproduction
2. Implement Single Fix — ONE change at a time, no "while I'm here" improvements
3. Verify Fix — Test passes? No other tests broken? Issue resolved?
4. If Fix Doesn't Work — If < 3 attempts: return to Phase 1. If ≥ 3: STOP and question the architecture
5. If 3+ Fixes Failed: Question Architecture — Is this pattern fundamentally sound? Discuss with human before more fixes.

Red Flags - STOP and Follow Process

• "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"
• Each fix reveals new problem in different place

ALL of these mean: 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"	First fix sets the pattern. Do it right from the start.
"Multiple fixes at once saves time"	Can't isolate what worked. Causes new bugs.
"I see the problem, let me fix it"	Seeing symptoms ≠ understanding root cause.

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

Real-World Impact

• 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