systematic-debugging

A four-phase method for debugging software by finding the root cause before changing code.

In plain words
What is it for?
Use it when tests fail, builds break, performance drops, integrations misbehave, or software produces unexpected results.
Why use it?
It reduces guesswork, repeated failed fixes, and patches that hide the real problem.

Skill for Claude CodeCodex

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/s3yed/appie-kit/systematic-debugging
Any agent
npx skills add S3YED/appie-kit --skill systematic-debugging
Clone the repo
git clone --depth 1 https://github.com/S3YED/appie-kit

Made for: Claude Code, Codex.

Per session 33 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,466 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 94% copy Near-identical to another mod 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 $0.00033 $0.02466
Opus 5 $0.00016 $0.01233
Sonnet 5 $0.00007 $0.00493
Haiku 4.5 $0.00003 $0.00247

Measured 2d ago against content hash 6ecb2d692e9e, 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 0 findings 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 2d ago.

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.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

94% identical to systematic-debugging — 20 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/automation/software-development/systematic-debugging/SKILL.md · 367 lines

How it starts

The opening of the file, as written. The whole thing — 367 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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.

Violating the letter of this process is violating the spirit of debugging.

The Iron Law

NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST

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

When to Use

Use for ANY technical issue:

  • Test failures
  • Bugs in production
  • Unexpected behavior
  • Performance problems
  • Build failures
  • Integration issues

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
  • You don't fully understand the issue

Don't skip when:

  • Issue seems simple (simple bugs have root causes too)
  • You're in a hurry (rushing guarantees rework)
  • Someone wants it fixed NOW (systematic is faster than thrashing)

The Four Phases

You MUST complete each phase before proceeding to the next.


Phase 1: Root Cause Investigation

BEFORE attempting ANY fix:

1. Read Error Messages Carefully

  • Don't skip past errors or warnings
  • They often contain the exact solution
  • Read stack traces completely
  • Note line numbers, file paths, error codes

Action: Use read_file on the relevant source files. Use search_files to find the error string in the codebase.

2. Reproduce Consistently

  • Can you trigger it reliably?
  • What are the exact steps?
  • Does it happen every time?
  • If not reproducible → gather more data, don't guess

Action: Use the terminal tool to run the failing test or trigger the bug:

# Run specific failing test
pytest tests/test_module.py::test_name -v

# Run with verbose output
pytest tests/test_module.py -v --tb=long

3. Check Recent Changes

  • What changed that could cause this?
  • Git diff, recent commits
  • New dependencies, config changes

Read the full file on GitHub · 367 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. 2d ago First seen · 367 lines · 33 tokens per session scan A 6ecb2d692e9e

Subscribe to this mod's changes

systematic-debugging is a skill published in the GitHub repository S3YED/appie-kit (6 stars, last pushed 6d ago), licensed MIT. It adds 33 tokens to every session and 2,466 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to systematic-debugging, differing in 20 lines, and is treated as a copy.

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