Systematic Debugging

--- name: systematic-debugging description: Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes --- # 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 - 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 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** **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):** `bash # 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 ### 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. **Create Failing Test Case** - Simplest possible reproduction - Automated test if possible - One-off test script if no framework - MUST have before fixing - Use the superpowers:test-driven-development` skill for writing proper fai