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skills/software-development/systematic-debugging/SKILL.md
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skills/software-development/systematic-debugging/SKILL.md
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---
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name: systematic-debugging
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description: Use when encountering any bug, test failure, or unexpected behavior. 4-phase root cause investigation — NO fixes without understanding the problem first.
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version: 1.1.0
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author: Hermes Agent (adapted from obra/superpowers)
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license: MIT
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metadata:
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hermes:
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tags: [debugging, troubleshooting, problem-solving, root-cause, investigation]
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related_skills: [test-driven-development, writing-plans, subagent-driven-development]
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---
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# Systematic Debugging
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## Overview
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Random fixes waste time and create new bugs. Quick patches mask underlying issues.
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**Core principle:** ALWAYS find root cause before attempting fixes. Symptom fixes are failure.
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**Violating the letter of this process is violating the spirit of debugging.**
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## The Iron Law
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```
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NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST
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```
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If you haven't completed Phase 1, you cannot propose fixes.
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## When to Use
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Use for ANY technical issue:
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- Test failures
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- Bugs in production
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- Unexpected behavior
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- Performance problems
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- Build failures
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- Integration issues
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**Use this ESPECIALLY when:**
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- Under time pressure (emergencies make guessing tempting)
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- "Just one quick fix" seems obvious
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- You've already tried multiple fixes
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- Previous fix didn't work
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- You don't fully understand the issue
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**Don't skip when:**
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- Issue seems simple (simple bugs have root causes too)
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- You're in a hurry (rushing guarantees rework)
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- Someone wants it fixed NOW (systematic is faster than thrashing)
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## The Four Phases
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You MUST complete each phase before proceeding to the next.
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---
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## Phase 1: Root Cause Investigation
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**BEFORE attempting ANY fix:**
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### 1. Read Error Messages Carefully
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- Don't skip past errors or warnings
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- They often contain the exact solution
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- Read stack traces completely
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- Note line numbers, file paths, error codes
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**Action:** Use `read_file` on the relevant source files. Use `search_files` to find the error string in the codebase.
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### 2. Reproduce Consistently
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- Can you trigger it reliably?
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- What are the exact steps?
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- Does it happen every time?
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- If not reproducible → gather more data, don't guess
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**Action:** Use the `terminal` tool to run the failing test or trigger the bug:
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```bash
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# Run specific failing test
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pytest tests/test_module.py::test_name -v
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# Run with verbose output
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pytest tests/test_module.py -v --tb=long
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```
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### 3. Check Recent Changes
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- What changed that could cause this?
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- Git diff, recent commits
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- New dependencies, config changes
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**Action:**
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```bash
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# Recent commits
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git log --oneline -10
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# Uncommitted changes
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git diff
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# Changes in specific file
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git log -p --follow src/problematic_file.py | head -100
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```
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### 4. Gather Evidence in Multi-Component Systems
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**WHEN system has multiple components (API → service → database, CI → build → deploy):**
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**BEFORE proposing fixes, add diagnostic instrumentation:**
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For EACH component boundary:
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- Log what data enters the component
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- Log what data exits the component
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- Verify environment/config propagation
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- Check state at each layer
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Run once to gather evidence showing WHERE it breaks.
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THEN analyze evidence to identify the failing component.
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THEN investigate that specific component.
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### 5. Trace Data Flow
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**WHEN error is deep in the call stack:**
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- Where does the bad value originate?
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- What called this function with the bad value?
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- Keep tracing upstream until you find the source
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- Fix at the source, not at the symptom
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**Action:** Use `search_files` to trace references:
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```python
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# Find where the function is called
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search_files("function_name(", path="src/", file_glob="*.py")
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# Find where the variable is set
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search_files("variable_name\\s*=", path="src/", file_glob="*.py")
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```
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### Phase 1 Completion Checklist
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- [ ] Error messages fully read and understood
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- [ ] Issue reproduced consistently
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- [ ] Recent changes identified and reviewed
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- [ ] Evidence gathered (logs, state, data flow)
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- [ ] Problem isolated to specific component/code
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- [ ] Root cause hypothesis formed
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**STOP:** Do not proceed to Phase 2 until you understand WHY it's happening.
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---
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## Phase 2: Pattern Analysis
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**Find the pattern before fixing:**
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### 1. Find Working Examples
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- Locate similar working code in the same codebase
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- What works that's similar to what's broken?
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**Action:** Use `search_files` to find comparable patterns:
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```python
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search_files("similar_pattern", path="src/", file_glob="*.py")
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```
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### 2. Compare Against References
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- If implementing a pattern, read the reference implementation COMPLETELY
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- Don't skim — read every line
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- Understand the pattern fully before applying
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### 3. Identify Differences
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- What's different between working and broken?
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- List every difference, however small
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- Don't assume "that can't matter"
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### 4. Understand Dependencies
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- What other components does this need?
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- What settings, config, environment?
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- What assumptions does it make?
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---
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## Phase 3: Hypothesis and Testing
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**Scientific method:**
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### 1. Form a Single Hypothesis
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- State clearly: "I think X is the root cause because Y"
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- Write it down
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- Be specific, not vague
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### 2. Test Minimally
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- Make the SMALLEST possible change to test the hypothesis
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- One variable at a time
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- Don't fix multiple things at once
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### 3. Verify Before Continuing
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- Did it work? → Phase 4
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- Didn't work? → Form NEW hypothesis
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- DON'T add more fixes on top
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### 4. When You Don't Know
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- Say "I don't understand X"
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- Don't pretend to know
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- Ask the user for help
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- Research more
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---
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## Phase 4: Implementation
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**Fix the root cause, not the symptom:**
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### 1. Create Failing Test Case
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- Simplest possible reproduction
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- Automated test if possible
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- MUST have before fixing
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- Use the `test-driven-development` skill
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### 2. Implement Single Fix
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- Address the root cause identified
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- ONE change at a time
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- No "while I'm here" improvements
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- No bundled refactoring
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### 3. Verify Fix
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```bash
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# Run the specific regression test
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pytest tests/test_module.py::test_regression -v
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# Run full suite — no regressions
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pytest tests/ -q
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```
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### 4. If Fix Doesn't Work — The Rule of Three
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- **STOP.**
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- Count: How many fixes have you tried?
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- If < 3: Return to Phase 1, re-analyze with new information
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- **If ≥ 3: STOP and question the architecture (step 5 below)**
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- DON'T attempt Fix #4 without architectural discussion
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### 5. If 3+ Fixes Failed: Question Architecture
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**Pattern indicating an architectural problem:**
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- Each fix reveals new shared state/coupling in a different place
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- Fixes require "massive refactoring" to implement
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- Each fix creates new symptoms elsewhere
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**STOP and question fundamentals:**
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- Is this pattern fundamentally sound?
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- Are we "sticking with it through sheer inertia"?
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- Should we refactor the architecture vs. continue fixing symptoms?
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**Discuss with the user before attempting more fixes.**
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This is NOT a failed hypothesis — this is a wrong architecture.
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---
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## Red Flags — STOP and Follow Process
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If you catch yourself thinking:
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- "Quick fix for now, investigate later"
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- "Just try changing X and see if it works"
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- "Add multiple changes, run tests"
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- "Skip the test, I'll manually verify"
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- "It's probably X, let me fix that"
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- "I don't fully understand but this might work"
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- "Pattern says X but I'll adapt it differently"
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- "Here are the main problems: [lists fixes without investigation]"
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- Proposing solutions before tracing data flow
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- **"One more fix attempt" (when already tried 2+)**
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- **Each fix reveals a new problem in a different place**
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**ALL of these mean: STOP. Return to Phase 1.**
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**If 3+ fixes failed:** Question the architecture (Phase 4 step 5).
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## Common Rationalizations
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| Excuse | Reality |
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|--------|---------|
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| "Issue is simple, don't need process" | Simple issues have root causes too. Process is fast for simple bugs. |
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| "Emergency, no time for process" | Systematic debugging is FASTER than guess-and-check thrashing. |
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| "Just try this first, then investigate" | First fix sets the pattern. Do it right from the start. |
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| "I'll write test after confirming fix works" | Untested fixes don't stick. Test first proves it. |
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| "Multiple fixes at once saves time" | Can't isolate what worked. Causes new bugs. |
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| "Reference too long, I'll adapt the pattern" | Partial understanding guarantees bugs. Read it completely. |
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| "I see the problem, let me fix it" | Seeing symptoms ≠ understanding root cause. |
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| "One more fix attempt" (after 2+ failures) | 3+ failures = architectural problem. Question the pattern, don't fix again. |
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## Quick Reference
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| Phase | Key Activities | Success Criteria |
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|-------|---------------|------------------|
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| **1. Root Cause** | Read errors, reproduce, check changes, gather evidence, trace data flow | Understand WHAT and WHY |
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| **2. Pattern** | Find working examples, compare, identify differences | Know what's different |
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| **3. Hypothesis** | Form theory, test minimally, one variable at a time | Confirmed or new hypothesis |
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| **4. Implementation** | Create regression test, fix root cause, verify | Bug resolved, all tests pass |
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## Hermes Agent Integration
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### Investigation Tools
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Use these Hermes tools during Phase 1:
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- **`search_files`** — Find error strings, trace function calls, locate patterns
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- **`read_file`** — Read source code with line numbers for precise analysis
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- **`terminal`** — Run tests, check git history, reproduce bugs
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- **`web_search`/`web_extract`** — Research error messages, library docs
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### With delegate_task
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For complex multi-component debugging, dispatch investigation subagents:
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```python
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delegate_task(
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goal="Investigate why [specific test/behavior] fails",
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context="""
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Follow systematic-debugging skill:
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1. Read the error message carefully
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2. Reproduce the issue
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3. Trace the data flow to find root cause
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4. Report findings — do NOT fix yet
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Error: [paste full error]
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File: [path to failing code]
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Test command: [exact command]
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""",
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toolsets=['terminal', 'file']
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)
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```
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### With test-driven-development
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When fixing bugs:
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1. Write a test that reproduces the bug (RED)
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2. Debug systematically to find root cause
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3. Fix the root cause (GREEN)
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4. The test proves the fix and prevents regression
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## Real-World Impact
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From debugging sessions:
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- Systematic approach: 15-30 minutes to fix
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- Random fixes approach: 2-3 hours of thrashing
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- First-time fix rate: 95% vs 40%
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- New bugs introduced: Near zero vs common
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**No shortcuts. No guessing. Systematic always wins.**
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