systematic-debugging
Helps your agent find and fix errors in programs. It analyzes unexpected behaviors before attempting repairs. Essential for ensuring software works correctly.
What it does
This tool helps find the real cause of technical problems, like program errors or unexpected behavior. It guides you to investigate before trying to fix, ensuring the solution is permanent, not just temporary.
When to use it
- ✓When a program shows an error you don't understand.
- ✓If you've already tried fixing something multiple times without success.
- ✓In emergency situations where the temptation for a quick fix is high.
Example of what to ask your AI
“My code is giving a strange error when I try to save a file, what should I do to investigate the root cause?”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
The tool suggests following organized steps: first, understand the error and how to reproduce it; then, check what changed recently. Only then, you form a hypothesis and test the smallest possible change to confirm the cause.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add sickn33/agentic-awesome-skills --skill systematic-debuggingOr download just the file:
curl -L https://raw.githubusercontent.com/sickn33/agentic-awesome-skills/main/plugins/agentic-awesome-skills-claude/skills/systematic-debugging/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
Systematic Debugging
Overview
Random fixes waste time and create new bugs. Quick patches mask underlying issues.
Core principle: Investigate before guessing and separate a verified repair from a temporary mitigation. During an incident, an authorized rollback or containment action may restore service while root-cause work continues.
Violating the letter of this process is violating the spirit of debugging.
The Iron Law
NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST
Start with the observable failure and the smallest useful evidence check. Label any emergency mitigation explicitly and preserve evidence for the later root-cause investigation.
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)
- Manager 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:
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
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
Check Recent Changes
- What changed that could cause this?
- Git diff, recent commits
- New dependencies, config changes
- Environmental differences
Gather Evidence in Multi-Component Systems
WHEN system has multiple components (CI → build → signing, API → service → database):
BEFORE proposing fixes, add diagnostic instrumentation:
For EACH component boundary: - Record allowed field names, sizes, statuses and correlation IDs - Redact secrets and private payloads before logging - Verify environment/config propagation - Check state at each layer Run once to gather evidence showing WHERE it breaks THEN analyze evidence to identify failing component THEN investigate that specific componentExample (multi-layer system):
# In each relevant process, report presence only; never dump secret values. if [ -n "${IDENTITY:-}" ]; then echo 'IDENTITY is set' else echo 'IDENTITY is absent or empty' fi # Read-only validation of an already-built artifact, when available. codesign --verify --verbose=2 "$APP"Interpretation: Compare presence checks at the actual workflow/build boundaries. Artifact verification does not itself prove that the correct signing identity propagated.
Trace Data Flow
WHEN error is deep in call stack:
See
root-cause-tracing.mdin this directory for the complete backward tracing technique.Quick version:
- Where does bad value originate?
- What called this with bad value?
- Keep tracing up until you find the source
- Fix at source, not at symptom
Phase 2: Pattern Analysis
Find the pattern before fixing:
Find Working Examples
- Locate similar working code in same codebase
- What works that's similar to what's broken?
Compare Against References
- If implementing pattern, read reference implementation COMPLETELY
- Don't skim - read every line
- Understand the pattern fully before applying
Identify Differences
- What's different between working and broken?
- List every difference, however small
- Don't assume "that can't matter"
Understand Dependencies
- What other components does this need?
- What settings, config, environment?
- What assumptions does it make?
Phase 3: Hypothesis and Testing
Scientific method:
Form Single Hypothesis
- State clearly: "I think X is the root cause because Y"
- Write it down
- Be specific, not vague
Test Minimally
- Make the SMALLEST possible change to test hypothesis
- One variable at a time
…
FAQ
Why can't I just try a quick fix?
Quick fixes can hide the real problem, lead to new bugs, and ultimately cost more time. Investigating the root cause ensures a lasting solution.
What is a 'root cause'?
It's the fundamental reason why a problem occurs. Instead of just treating the symptom (the visible error), the root cause is the original issue that, if fixed, prevents the error from happening again.
What if the problem involves multiple parts of a system?
The tool asks to check communication between parts, logging information at each 'boundary' (where one part talks to another) to see where the failure first occurs.
Details
Original description by the author
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes
Popularity
- GitHub stars
- 48k
- Ranking position
- #4304
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
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