debug-mastery - SKILL.md Agent Skill

name: debug-mastery description: Systematic debugging methodology with 4-phase process, root cause tracing, and elite observability standards. No fixes without investigation. allowed-tools: Read, Write, Edit, Glob, Grep, Bash

# 🐛 DEBUG MASTERY: SYSTEMATIC DEBUGGING > **Philosophy:** Random fixes waste time and create new bugs. Quick patches mask underlying issues. ALWAYS find root cause before attempting fixes. **FORENSIC ANALYSIS MANDATE (CRITICAL):** Never apply a fix without a confirmed root cause. AI-generated fixes often address symptoms rather than underlying architectural logic. You MUST perform a 'Forensic Investigation' that identifies the specific assumption or boundary condition that failed. For every fix, you must provide a brief analysis note explaining WHY the original architecture allowed the bug to exist, transforming every error into a systemic engineering lesson. --- ## 🚨 THE IRON LAW ``` NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST ``` If you haven't completed Phase 1, you cannot propose fixes. **Violating the letter of this process is violating the spirit of debugging.** --- ## 📋 WHEN TO USE Use for ANY technical issue: - Test failures - Bugs in production - Unexpected behavior - Performance problems - Build failures - Integration issues **Use 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 (systematic is faster than thrashing) - Manager wants it fixed NOW (systematic is faster than guess-and-check) ## 🔄 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 ``` 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 - 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 `@tdd-mastery` skill for writing proper failing tests 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** - Test passes now? - 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 user 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) --- ## 🚫 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 | --- ## 🛠️ SUPPORTING TECHNIQUES These techniques are part of systematic debugging: - **`@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 --- ## 🛰️ OBSERVABILITY TOOLING ### Precision Logging (JSON-First) **Mandatory Fields:** `timestamp`, `level`, `traceId`, `component`, `message`, `context` **Log Levels:** - **ERROR:** System failure, data loss, crash. Immediate audit required. - **WARN:** Recoverable anomaly (retry, fallback triggered). - **INFO:** Significant state change (phase transition, tool started). - **DEBUG:** Detailed execution path, raw payloads, environment. ### Distributed Tracing 1. **Propagation:** Every request/action carries `TraceID` 2. **Span Definition:** Wrap tool calls and complex logic to measure latency ### Domain-Specific Troubleshooting **Frontend:** - Time-Travel: Redux DevTools, state snapshots - Visual Regression: `ux-audit.js` for layout shifts **Backend:** - eBPF Observability: Kernel-level IO/Network tracing - Transaction Audits: ACID compliance verification **Extensions (MV3):** - Service Worker: Verify `chrome.alarms` pulses - Context Bridge: Check "Disconnected Port" errors --- ## 📈 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 --- ## 🔗 RELATED SKILLS - **@tdd-mastery** - For creating failing test case (Phase 4, Step 1) - **@verification-mastery** - Verify fix worked before claiming success - **@clean-code** - Prevent bugs through good practices