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systematic-debugging

Trace failures backward through call chains to identify root causes.

2|1|Updated Apr 22, 2026
Search Tags:#debugging#root cause#bug fix#stack trace#test failure#reproduction
One-click install
npx skills add https://github.com/pytholic/claude-skills --skill systematic-debugging-pytholic
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: systematic-debugging
Source: https://github.com/pytholic/claude-skills/tree/main/systematic-debugging
Command: npx skills add https://github.com/pytholic/claude-skills --skill systematic-debugging-pytholic

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides a disciplined debugging workflow for identifying the true origin of bugs, test failures, runtime errors, and unexpected behavior instead of applying quick patches at the crash site.

Core Features & Use Cases

  • Root Cause Analysis: Trace failures backward through stack frames and data flow until the first invalid state is found.
  • Hypothesis-Driven Fixes: Require an explicit evidence-backed hypothesis before making any implementation change.
  • Safe Verification: Reproduce the issue with a minimal failing test, implement one targeted fix, and validate the result against the full test suite.
  • Use Case: When a test starts failing after a refactor, use this Skill to reproduce the failure, isolate the exact input or boundary that breaks, and fix the source of the bug without masking symptoms.

Quick Start

Use the systematic-debugging skill to investigate this failing error and identify the root cause before proposing any fix.

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 the crash site?▼

Root cause debugging requires reproducing the failure, tracing invalid state backward through the call chain, and isolating the first invalid state before attempting any fix. This prevents masking symptoms with quick patches at the crash site.

How do I debug a failing test after a code refactor?▼

Debug failing tests by reproducing the failure with a minimal test case, isolating the exact input or boundary condition that breaks, and tracing the invalid data flow backward to the source of the bug.

What is the best way to fix a runtime error using a systematic debugging workflow?▼

Systematic debugging fixes runtime errors by forming an explicit evidence-backed hypothesis, implementing one targeted fix, and validating the result against the full test suite to ensure no regressions occur.

Can I use this debugging workflow for stack traces across different programming languages?▼

Yes, the debugging workflow applies language-agnostic tracing of stack frames and data flow, requiring an evidence-backed hypothesis and targeted reproduction to identify the root cause across any runtime environment.

Why do my bug fixes keep causing new test failures and regressions?▼

Fixes cause regressions when symptoms are patched without identifying the root cause. Safe verification requires reproducing the issue with a minimal failing test and validating the targeted fix against the full test suite.

When should I not apply a quick patch to a runtime error?▼

You should not patch a runtime error without an explicit evidence-backed hypothesis. Tracing the invalid state backward through the call chain is required to ensure the fix resolves the original failure without masking underlying symptoms.

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