Debugging Wizard

CommunityPopular

Jeffallan

debugging-wizard

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.

Overview

Publisher	Jeffallan
Repository	`claude-skills`
Skill name	`debugging-wizard`
Stars	11.5K
Forks	1.1K
Bundled files	5
License	MIT
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
5 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by Jeffallan on GitHub. Read the source before you install it.

Installation

Install the Debugging Wizard AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/Jeffallan/claude-skills.git /tmp/claude-skills
mkdir -p .claude/skills
cp -r /tmp/claude-skills/skills/debugging-wizard .claude/skills/debugging-wizard

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Debugging Wizard in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Debugging Wizard on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Debugging Wizard is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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:

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)

bash
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)

bash
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)

bash
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)

bash
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

Documentation

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Debugging Wizard AI skill do?

Why use Debugging Wizard on TypingMind?

Because you install it once and use it with any model. Debugging Wizard is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Debugging Wizard in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Jeffallan/claude-skills/tree/main/skills/debugging-wizard. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Debugging Wizard?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Debugging Wizard?

As many as you like. As long as a model supports skills, you can use Debugging Wizard with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Debugging Wizard AI skill free?

Yes. It is published on GitHub by Jeffallan under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Systematic Debugging

obra

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Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes

Test Driven Development

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Use when implementing any feature or bugfix, before writing implementation code

Using Git Worktrees

Use when starting feature work that needs isolation from current workspace or before executing implementation plans - ensures an isolated workspace exists via native tools or git worktree fallback

Using Superpowers

Use when starting any conversation - establishes how to find and use skills, requiring skill invocation before ANY response including clarifying questions

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Debugging Wizard

Core Workflow

Reference Guide

Constraints

MUST DO

MUST NOT DO

Common Debugging Commands

Output Templates

Bundled files

Frequently asked questions

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