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Agent skill

Systematic Debugging

by bobmatnyc in bobmatnyc/claude-mpm

Methodical debugging instead of random changes. An agent skill from bobmatnyc/claude-mpm.

MITAuto-check passedDevelopment

Install Systematic Debugging

skills CLI
$ npx skills add bobmatnyc/claude-mpm --skill systematic-debugging -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install bobmatnyc/claude-mpm systematic-debugging --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/bobmatnyc/claude-mpm.git skills-src && mkdir -p .claude/skills && cp -r skills-src/src/claude_mpm/skills/bundled/debugging/systematic-debugging .claude/skills/systematic-debugging && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
systematic-debugging
GitHub stars
155
Token cost
~1.3k tokens
SKILL.md length
544 words
Files
5 (incl. references)
Skills in repo
63
Repo updated
First seen
Licence
MIT

At a glance

Methodical debugging instead of random changes. An agent skill from bobmatnyc/claude-mpm.

  • Works in 4 steps: Root Cause Investigation → Pattern Analysis → Hypothesis and Testing → …
  • Tasks that involve Debugging
  • SKILL.md covers Overview, When to Use This Skill, The Iron Law and Core Principles, plus 7 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Systematic Debugging is an agent skill from bobmatnyc/claude-mpm. Methodical debugging instead of random changes

Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `references/anti-patterns.md`, `references/examples.md` and `references/troubleshooting.md`).

It sits in Development, covering Debugging. The repository describes itself as: Claude Multi-Agent Project Manager — multi-channel orchestration, GitHub-first SDK mode, and plugin system for Claude. The licence is MIT.

When your agent uses it

  • Tasks that involve Debugging

Example prompts

  • “/systematic-debugging”

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Root Cause Investigation
  2. Pattern Analysis
  3. Hypothesis and Testing
  4. Implementation

What it can do on your machine

Read from SKILL.md and the folder at commit 25203d3. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Systematic Debugging loads about 1.3k tokens when it runs, and up to ~13k if it reads all its reference files. Until then it costs about 17 tokens; SKILL.md has 544 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~17
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~13k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from bobmatnyc/claude-mpm at commit 25203d3, republished under its MIT licence (© bobmatnyc). 544 words, ~1,290 tokens.

Download SKILL.mdSave it as .claude/skills/systematic-debugging/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
systematic-debugging
description
Methodical debugging instead of random changes
version
2.2.0
category
debugging
author
Jesse Vincent
license
MIT
source
https://github.com/obra/superpowers-skills/tree/main/skills/debugging/systematic-debugging
progressive_disclosure.references
workflow.md, examples.md, troubleshooting.md, anti-patterns.md
context_limit
800
tags
debugging, problem-solving, root-cause, systematic
requires_tools
debugger
effort
high

Systematic Debugging

Overview

Random fixes waste time and create new bugs. Quick patches mask underlying issues.

Core principle: ALWAYS find root cause before attempting fixes. Symptom fixes are failure.

This skill enforces a four-phase systematic approach that ensures root cause investigation before any fix attempt. Violating the letter of this process is violating the spirit of debugging.

When to Use This Skill

Activate when:

  • User reports a bug or error
  • Test failures occur
  • Code behaves unexpectedly
  • Performance problems arise
  • Build or integration failures
  • User says "it's not working"

Use this ESPECIALLY when:

  • Under time pressure (emergencies make guessing tempting)
  • "Just one quick fix" seems obvious
  • You've already tried multiple fixes
  • Previous fix didn't work

The Iron Law

NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST

If you haven't completed Phase 1, you cannot propose fixes.

Core Principles

  1. Reproduce First: Ensure you can reliably reproduce the issue
  2. One Change at a Time: Change only one thing between tests
  3. Hypothesis-Driven: Form hypotheses before making changes
  4. Verify Fixes: Confirm the fix works and doesn't break anything else

Quick Start

  1. Read Error Messages: Read completely, including stack traces
  2. Reproduce Consistently: Create reliable reproduction steps
  3. Gather Evidence: Add diagnostic instrumentation in multi-component systems
  4. Form Hypothesis: State clearly "I think X because Y"
  5. Test Minimally: Make smallest possible change
  6. Verify Fix: Confirm resolution and no regressions

The Four Phases

Phase 1: Root Cause Investigation

BEFORE attempting ANY fix:

  • Read error messages carefully (they often contain the solution)
  • Reproduce consistently
  • Check recent changes
  • Gather evidence in multi-component systems
  • Trace data flow back to source
Phase 2: Pattern Analysis

Find working examples, compare against references, identify differences, understand dependencies.

Phase 3: Hypothesis and Testing

Form single hypothesis, test minimally (one variable at a time), verify before continuing.

Phase 4: Implementation

Create failing test case, implement single fix addressing root cause, verify fix works.

If 3+ fixes fail: STOP and question the architecture - this indicates architectural problems, not failed hypotheses.

Show full SKILL.md (221 more words)Show less

Navigation

For detailed information:

  • Workflow: Complete four-phase debugging workflow with decision trees and detailed steps
  • Examples: Real-world debugging scenarios with step-by-step walkthroughs
  • Troubleshooting: Common debugging challenges and how to overcome them
  • Anti-patterns: Common mistakes, rationalizations, and red flags

Key Reminders

  • NEVER make random changes hoping they'll work
  • ALWAYS reproduce the issue before attempting fixes
  • Form hypothesis BEFORE making changes
  • Change ONE thing at a time
  • Verify fix actually resolves the issue
  • Check for regressions after fixing
  • If 3+ fixes fail, question the architecture

Red Flags - STOP and Follow Process

If you catch yourself thinking:

  • "Quick fix for now, investigate later"
  • "Just try changing X and see if it works"
  • "It's probably X, let me fix that"
  • "I don't fully understand but this might work"
  • "One more fix attempt" (when already tried 2+)
  • Each fix reveals new problem in different place

ALL of these mean: STOP. Return to Phase 1.

Integration with Other Skills

  • root-cause-tracing: How to trace back through call stack
  • defense-in-depth: Add validation after finding root cause
  • condition-based-waiting: Replace timeouts identified in Phase 2
  • verification-before-completion: Verify fix worked before claiming success
  • test-driven-development: Create failing test case in Phase 4

Real-World Impact

From debugging sessions:

  • Systematic approach: 15-30 minutes to fix
  • Random fixes approach: 2-3 hours of thrashing
  • First-time fix rate: 95% vs 40%
  • New bugs introduced: Near zero vs common

© bobmatnyc, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (references) in src/claude_mpm/skills/bundled/debugging/systematic-debugging of bobmatnyc/claude-mpm.

  • SKILL.md
  • references/anti-patterns.md
  • references/examples.md
  • references/troubleshooting.md
  • references/workflow.md

Open the folder on GitHubat commit 25203d3

Compare with similar skills

Systematic Debugging next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Systematic Debugging compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Systematic Debugging this skillbobmatnyc/claude-mpm155—~1.3kAutomated safety check: PassMIT
Trellis Session Insightmindfold-ai/Trellis15k4 repos~1.7kAutomated safety check: PassAGPL-3.0
Native Data FetchingCherryHQ/cherry-studio-app4k6 repos~2.9kAutomated safety check: NotesMIT
Aoti Debugpytorch/pytorch104k1 repos~1.7kAutomated safety check: PassCustom licence
Herdr Throwaway Reproductionherdrdev/herdr43k—~2.4kAutomated safety check: PassApache-2.0
Systematic Debuggingultralisp/ultralisp25851 repos~2.4kAutomated safety check: PassNone

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Categories

Questions about Systematic Debugging

What does Systematic Debugging do?

Methodical debugging instead of random changes. An agent skill from bobmatnyc/claude-mpm. Systematic Debugging is an agent skill from bobmatnyc/claude-mpm.

When should I use Systematic Debugging?

Systematic Debugging fits situations like: tasks that involve Debugging.

How do I install Systematic Debugging in Claude Code?

Run `npx skills add bobmatnyc/claude-mpm --skill systematic-debugging -a claude-code`. Or copy the skill folder (src/claude_mpm/skills/bundled/debugging/systematic-debugging in bobmatnyc/claude-mpm) into .claude/skills/systematic-debugging in your project. Claude Code loads it when a task matches its description.

How do I install Systematic Debugging in Codex?

Run `npx skills add bobmatnyc/claude-mpm --skill systematic-debugging -a codex`. Or copy the skill folder (src/claude_mpm/skills/bundled/debugging/systematic-debugging in bobmatnyc/claude-mpm) into .agents/skills/systematic-debugging in your project. Codex loads it when a task matches its description.

Can I use Systematic Debugging in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add bobmatnyc/claude-mpm --skill systematic-debugging -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/systematic-debugging, .gemini/skills/systematic-debugging, .github/skills/systematic-debugging and .opencode/skills/systematic-debugging in your project.

What does Systematic Debugging need to run?

SKILL.md names no scripts, command-line tools or credentials: Systematic Debugging is instructions for the agent only.

Does Systematic Debugging access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Systematic Debugging safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Systematic Debugging use?

Systematic Debugging is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Systematic Debugging use?

About 1.3k tokens (SKILL.md is roughly 5.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 11k tokens, read only when the agent opens those files.

What are the alternatives to Systematic Debugging?

Skills that share tags, products or a category with Systematic Debugging: Trellis Session Insight (mindfold-ai/Trellis, 15k stars), Native Data Fetching (CherryHQ/cherry-studio-app, 4k stars), Aoti Debug (pytorch/pytorch, 104k stars) and Herdr Throwaway Reproduction (herdrdev/herdr, 43k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Systematic Debugging?

bobmatnyc (a GitHub user) maintains it in bobmatnyc/claude-mpm, which has 155 GitHub stars. The repository holds 63 skills in this directory. The repository was last updated on August 31, 2026.

Source: bobmatnyc/claude-mpm on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.