systematic-debugging

systematic-debugging is a skill for Claude Code, Codex from MadAppGang/claude-code. It costs 39 tokens per session (4,489 once invoked), scanned A, original, MIT.

A step-by-step method for investigating software failures by tracing their underlying cause and checking proposed fixes.

In plain words
What is it for?
It helps investigate failed tests, errors, unexpected behavior, performance slowdowns, data corruption, and bugs that return after a fix.
Why use it?
It reduces trial-and-error debugging, such as changing unrelated code, clearing caches, or restarting tools without understanding the problem.

Skill for Claude CodeCodex

Part of the dev plugin — 47 skills, 12 commands, 14 agents shipped together

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/madappgang/claude-code/systematic-debugging
Any agent
npx skills add MadAppGang/claude-code --skill systematic-debugging
Clone the repo
git clone --depth 1 https://github.com/MadAppGang/claude-code

Made for: Claude Code, Codex.

Or install dev, the plugin that ships this one along with the rest of its 47 skills, 12 commands, 14 agents.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for systematic-debugging

README.md
[![agentmods](https://agentmods.dev/badge/skills/madappgang/claude-code/systematic-debugging.svg)](https://agentmods.dev/skills/madappgang/claude-code/systematic-debugging)
Your own site
<a href="https://agentmods.dev/skills/madappgang/claude-code/systematic-debugging"><img src="https://agentmods.dev/badge/skills/madappgang/claude-code/systematic-debugging.svg" alt="Measured on agentmods" height="20"></a>
Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,489 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00039 $0.04489
Opus 5 $0.00019 $0.02244
Sonnet 5 $0.00008 $0.00898
Haiku 4.5 $0.00004 $0.00449

Measured yesterday against content hash 174f089baeb7, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

systematic-debugging scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

response = requests.get('https://api.example.com/users')
plugins/dev/skills/discipline/systematic-debugging/SKILL.md · 577 lines

How it starts

The opening of the file, as written. The whole thing — 577 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Systematic Debugging

Iron Law: "NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST"

When to Use

Use this skill when:

  • A test fails and you need to understand why
  • An error is thrown and you need to find the cause
  • A feature behaves unexpectedly
  • Performance degrades and you need to identify bottlenecks
  • Data corruption occurs and you need to trace the source
  • A bug reappears after "fixing" it

Red Flags (Violation Indicators)

Detect these patterns that indicate skipping root cause investigation:

  • Fix without understanding - "I'll just add a null check" (why is it null?)
  • Skip to solution - "Let me try wrapping this in setTimeout" (why does timing matter?)
  • Restart tools - "Let me restart the dev server" (what state is corrupted?)
  • Clear cache - "Let me clear the cache" (what cache entry is stale?)
  • Change multiple things - "Let me update these 3 files" (which one fixes it?)
  • Shouldn't cause problem - "This change shouldn't affect that" (but it does, why?)
  • Assume cause - "Must be a race condition" (what evidence supports this?)

Key Concepts

1. Root Cause vs. Symptom

Symptom: What you observe (test fails, error thrown, wrong output) Root Cause: Why it happens (null value, wrong condition, missing await)

Example:

Symptom: "TypeError: Cannot read property 'name' of undefined"
Root Cause: API returns null when user not found, but code expects object

Bad approach: Add user?.name (fixes symptom, not cause) Good approach: Add validation if (!user) throw new NotFoundError() (fixes cause)

2. Data Flow Tracing

Principle: Follow data from source to error point

Steps:

  1. Identify error location (stack trace line number)
  2. Identify data involved (variable name, object property)
  3. Trace backwards: Where does this data come from?
  4. Find divergence: Where does actual differ from expected?

Example:

Error: "Expected 'active' but got 'inactive'"
Location: user.test.ts:42 - expect(user.status).toBe('active')
Data: user.status = 'inactive'
Trace: user.status ← updateUser() ← API response ← database
Divergence: Database has status='inactive' (expected 'active')
Root Cause: Test setup didn't create user with active status

Read the full file on GitHub · 577 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 577 lines · 39 tokens per session scan A 174f089baeb7

Subscribe to this mod's changes

systematic-debugging is a skill published in the GitHub repository MadAppGang/claude-code (279 stars, last pushed 5mo ago), licensed MIT. It adds 39 tokens to every session and 4,489 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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