| name | code-showcase-systematic-debugging |
| description | Four-phase debugging methodology with root cause analysis. Use when investigating bugs, fixing test failures, or troubleshooting unexpected behavior. Emphasizes NO FIXES WITHOUT ROOT CAUSE FIRST. |
| risk | unknown |
| source | https://github.com/ChrisWiles/claude-code-showcase/tree/main/.claude/skills/systematic-debugging |
| source_repo | ChrisWiles/claude-code-showcase |
| source_type | community |
| date_added | "2026-07-01T00:00:00.000Z" |
| license | MIT |
| license_source | https://github.com/ChrisWiles/claude-code-showcase/blob/main/LICENSE |
Systematic Debugging
When to Use
Use this skill when you need four-phase debugging methodology with root cause analysis. Use when investigating bugs, fixing test failures, or troubleshooting unexpected behavior. Emphasizes NO FIXES WITHOUT ROOT CAUSE FIRST.
Core Principle
NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST.
Never apply symptom-focused patches that mask underlying problems. Understand WHY something fails before attempting to fix it.
The Four-Phase Framework
Phase 1: Root Cause Investigation
Before touching any code:
- Read error messages thoroughly - Every word matters
- Reproduce the issue consistently - If you can't reproduce it, you can't verify a fix
- Examine recent changes - What changed before this started failing?
- Gather diagnostic evidence - Logs, stack traces, state dumps
- Trace data flow - Follow the call chain to find where bad values originate
Root Cause Tracing Technique:
1. Observe the symptom - Where does the error manifest?
2. Find immediate cause - Which code directly produces the error?
3. Ask "What called this?" - Map the call chain upward
4. Keep tracing up - Follow invalid data backward through the stack
5. Find original trigger - Where did the problem actually start?
Key principle: Never fix problems solely where errors appear—always trace to the original trigger.
Phase 2: Pattern Analysis
- Locate working examples - Find similar code that works correctly
- Compare implementations completely - Don't just skim
- Identify differences - What's different between working and broken?
- Understand dependencies - What does this code depend on?
Phase 3: Hypothesis and Testing
Apply the scientific method:
- Formulate ONE clear hypothesis - "The error occurs because X"
- Design minimal test - Change ONE variable at a time
- Predict the outcome - What should happen if hypothesis is correct?
- Run the test - Execute and observe
- Verify results - Did it behave as predicted?
- Iterate or proceed - Refine hypothesis if wrong, implement if right
Phase 4: Implementation
