systematic-debugging
4-phase systematic debugging methodology with root cause analysis and evidence-based verification. Use when debugging complex issues.
Best use case
systematic-debugging is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
4-phase systematic debugging methodology with root cause analysis and evidence-based verification. Use when debugging complex issues.
Teams using systematic-debugging should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/systematic-debugging/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How systematic-debugging Compares
| Feature / Agent | systematic-debugging | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
4-phase systematic debugging methodology with root cause analysis and evidence-based verification. Use when debugging complex issues.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Systematic Debugging > Source: obra/superpowers ## Overview This skill provides a structured approach to debugging that prevents random guessing and ensures problems are properly understood before solving. ## 4-Phase Debugging Process ### Phase 1: Reproduce Before fixing, reliably reproduce the issue. ```markdown ## Reproduction Steps 1. [Exact step to reproduce] 2. [Next step] 3. [Expected vs actual result] ## Reproduction Rate - [ ] Always (100%) - [ ] Often (50-90%) - [ ] Sometimes (10-50%) - [ ] Rare (<10%) ``` ### Phase 2: Isolate Narrow down the source. ```markdown ## Isolation Questions - When did this start happening? - What changed recently? - Does it happen in all environments? - Can we reproduce with minimal code? - What's the smallest change that triggers it? ``` ### Phase 3: Understand Find the root cause, not just symptoms. ```markdown ## Root Cause Analysis ### The 5 Whys 1. Why: [First observation] 2. Why: [Deeper reason] 3. Why: [Still deeper] 4. Why: [Getting closer] 5. Why: [Root cause] ``` ### Phase 4: Fix & Verify Fix and verify it's truly fixed. ```markdown ## Fix Verification - [ ] Bug no longer reproduces - [ ] Related functionality still works - [ ] No new issues introduced - [ ] Test added to prevent regression ``` ## Debugging Checklist ```markdown ## Before Starting - [ ] Can reproduce consistently - [ ] Have minimal reproduction case - [ ] Understand expected behavior ## During Investigation - [ ] Check recent changes (git log) - [ ] Check logs for errors - [ ] Add logging if needed - [ ] Use debugger/breakpoints ## After Fix - [ ] Root cause documented - [ ] Fix verified - [ ] Regression test added - [ ] Similar code checked ``` ## Common Debugging Commands ```bash # Recent changes git log --oneline -20 git diff HEAD~5 # Search for pattern grep -r "errorPattern" --include="*.ts" # Check logs pm2 logs app-name --err --lines 100 ``` ## Anti-Patterns ❌ **Random changes** - "Maybe if I change this..." ❌ **Ignoring evidence** - "That can't be the cause" ❌ **Assuming** - "It must be X" without proof ❌ **Not reproducing first** - Fixing blindly ❌ **Stopping at symptoms** - Not finding root cause
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