debugging-wizard
jeffallan/claude-skills
Systematic debugging methodology to isolate root causes and resolve bugs efficiently.
What is debugging-wizard?
Debugging Wizard applies structured hypothesis-driven analysis to error messages, stack traces, and logs to identify failure points. Use when investigating crashes, analyzing unexpected behavior, performing root cause analysis, or troubleshooting complex issues across any codebase.
- Parses error messages and stack traces to identify execution flow
- Correlates log entries to pinpoint failure points
- Applies systematic hypothesis-driven methodology to isolate bugs
- Guides reproduction, isolation, hypothesis testing, and fix verification
- Provides language-specific debugging tools and commands (Python pdb, Node.js Inspector, Git bisect, Go delve)
- Enforces regression prevention through test creation and safeguard documentation
How to install debugging-wizard
npx skills add https://github.com/jeffallan/claude-skills --skill debugging-wizardHow to use debugging-wizard
- 1.Reproduce the issue consistently with clear steps
- 2.Gather complete error messages, stack traces, and relevant logs
- 3.Narrow down to the smallest failing case using isolation techniques
- 4.Form one testable hypothesis at a time and verify or disprove it
- 5.Implement the fix and verify the solution resolves the issue
- 6.Add regression tests or safeguards to prevent recurrence
- 7.Remove all debug code before committing
Use cases
- Investigating application crashes with incomplete error messages
- Analyzing stack traces to trace execution flow and identify the exact failure point
- Hunting regressions using git bisect to find the commit that introduced a bug
- Correlating multiple log entries across services to find root cause in distributed systems
- Troubleshooting intermittent bugs by establishing consistent reproduction steps
- Backend developers debugging production issues
- QA engineers performing root cause analysis
- Full-stack developers investigating cross-layer failures
- DevOps engineers troubleshooting deployment or runtime errors
- Any developer systematically resolving complex or elusive bugs
debugging-wizard FAQ
Use Debugging Wizard for complex issues, stack traces you don't immediately understand, intermittent bugs, or when multiple failed fix attempts suggest a deeper root cause. For simple errors, the quick-fixes reference may suffice.
Reproduction is the first step. Gather all available logs, error messages, and context. Use systematic strategies like binary search (git bisect) or time-travel debugging to narrow down when/where it occurs, then work toward consistent reproduction.
Form one testable hypothesis at a time, test it, and document the result before moving to the next. This prevents masking the real issue and ensures you understand what actually fixed it.
Python (pdb), JavaScript/Node.js (Chrome DevTools Inspector), Git (bisect for regression hunting), and Go (delve). Language-specific tools and strategies are in the references.
No. The MUST NOT list explicitly forbids leaving console.log, debugger statements, or debug code in commits. Debug locally, then remove all debugging artifacts before committing.
Full instructions (SKILL.md)
Source of truth, from jeffallan/claude-skills.
name: debugging-wizard description: Parses error messages, traces execution flow through stack traces, correlates log entries to identify failure points, and applies systematic hypothesis-driven methodology to isolate and resolve bugs. Use when investigating errors, analyzing stack traces, finding root causes of unexpected behavior, troubleshooting crashes, or performing log analysis, error investigation, or root cause analysis. license: MIT metadata: author: https://github.com/Jeffallan version: "1.1.0" domain: quality triggers: debug, error, bug, exception, traceback, stack trace, troubleshoot, not working, crash, fix issue role: specialist scope: analysis output-format: analysis related-skills: test-master, fullstack-guardian, monitoring-expert
Debugging Wizard
Expert debugger applying systematic methodology to isolate and resolve issues in any codebase.
Core Workflow
- Reproduce - Establish consistent reproduction steps
- Isolate - Narrow down to smallest failing case
- Hypothesize and test - Form testable theories, verify/disprove each one
- Fix - Implement and verify solution
- Prevent - Add tests/safeguards against regression
Reference Guide
Load detailed guidance based on context:
<!-- Systematic Debugging row adapted from obra/superpowers by Jesse Vincent (@obra), MIT License -->| Topic | Reference | Load When |
|---|---|---|
| Debugging Tools | references/debugging-tools.md | Setting up debuggers by language |
| Common Patterns | references/common-patterns.md | Recognizing bug patterns |
| Strategies | references/strategies.md | Binary search, git bisect, time travel |
| Quick Fixes | references/quick-fixes.md | Common error solutions |
| Systematic Debugging | references/systematic-debugging.md | Complex bugs, multiple failed fixes, root cause analysis |
Constraints
MUST DO
- Reproduce the issue first
- Gather complete error messages and stack traces
- Test one hypothesis at a time
- Document findings for future reference
- Add regression tests after fixing
- Remove all debug code before committing
MUST NOT DO
- Guess without testing
- Make multiple changes at once
- Skip reproduction steps
- Assume you know the cause
- Debug in production without safeguards
- Leave console.log/debugger statements in code
Common Debugging Commands
Python (pdb)
python -m pdb script.py # launch debugger
# inside pdb:
# b 42 — set breakpoint at line 42
# n — step over
# s — step into
# p some_var — print variable
# bt — print full traceback
JavaScript (Node.js)
node --inspect-brk script.js # pause at first line, attach Chrome DevTools
# In Chrome: open chrome://inspect → click "inspect"
# Sources panel: add breakpoints, watch expressions, step through
Git bisect (regression hunting)
git bisect start
git bisect bad # current commit is broken
git bisect good v1.2.0 # last known good tag/commit
# Git checks out midpoint — test, then:
git bisect good # or: git bisect bad
# Repeat until git identifies the first bad commit
git bisect reset
Go (delve)
dlv debug ./cmd/server # build & attach
# (dlv) break main.go:55
# (dlv) continue
# (dlv) print myVar
Output Templates
When debugging, provide:
- Root Cause: What specifically caused the issue
- Evidence: Stack trace, logs, or test that proves it
- Fix: Code change that resolves it
- Prevention: Test or safeguard to prevent recurrence
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