systematic-debugging

Diagnose root causes of bugs using hypothesis-driven debugging phases.

Updated Mar 27, 2026
One-click install
npx skills add https://github.com/erenisiklar/Pusula --skill systematic-debugging-erenisiklar
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: systematic-debugging
Source: https://github.com/erenisiklar/Pusula/tree/main/.claude/skills/systematic-debugging
Command: npx skills add https://github.com/erenisiklar/Pusula --skill systematic-debugging-erenisiklar

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Four-phase hypothesis-driven debugging methodology with root cause analysis. Activates when investigating bugs, fixing test failures, diagnosing runtime errors, troubleshooting unexpected behavior, analyzing performance issues, or resolving race conditions. Enforces NO FIXES WITHOUT ROOT CAUSE FIRST.

Core Features & Use Cases

  • Phase 1: Root Cause Investigation — read error messages thoroughly, reproduce the issue consistently, examine recent changes, gather diagnostic evidence, and trace data flow to the origin.
  • Phase 2: Pattern Analysis — locate working examples, compare implementations completely, list all differences, understand dependencies, and check underlying assumptions.
  • Phase 3: Hypothesis and Testing — formulate ONE clear hypothesis, design a minimal test, predict the outcome, run the test, compare actual vs expected, and iterate as needed.
  • Phase 4: Implementation — create a fix only after root cause confirmation, verify with tests, and perform a brief post-mortem to prevent regression.
  • Use cases include debugging runtime errors, failing tests, performance issues, race conditions, and unexpected behavior in complex systems.

Quick Start

Reproduce the issue, document the error messages, formulate one hypothesis, and validate it with a minimal, verifiable change.

Frequently Asked Questions about systematic-debugging

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I find the root cause of a bug instead of just patching symptoms?

Root-cause debugging requires a structured, hypothesis-driven methodology that enforces no fixes without identifying the origin first. You reproduce the issue consistently, trace data flow, and gather diagnostic evidence before implementing any corrective actions.

How do I reproduce a runtime error consistently for structured debugging?

Consistent reproduction is the first phase of hypothesis-driven debugging. You read error messages thoroughly, examine recent changes, and trace data flow to the origin to ensure the issue is deterministic before formulating a hypothesis.

Can I fix failing tests without doing a full root cause analysis?

No, this methodology enforces no fixes without root cause confirmation. You must formulate one clear hypothesis, design a minimal test, predict the outcome, and compare actual versus expected results before creating a fix.

How to compare working code against failing implementations to diagnose unexpected behavior?

Pattern analysis involves locating working examples, comparing implementations completely, listing all differences, understanding dependencies, and checking underlying assumptions to isolate why the failure occurs.

Why should I perform a post-mortem after resolving a bug?

A brief post-mortem prevents regression after you verify the fix with tests. It concludes the implementation phase by documenting the root cause and corrective action to avoid similar issues across the codebase.