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KarlinskyS
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systematic-debugging

Diagnoses bugs via a four-phase root-cause investigation workflow.

Updated Apr 10, 2026
Search Tags:#debugging#diagnostics#evidence#phases#root-cause#reproduction#data-flow
One-click install
npx skills add https://github.com/KarlinskyS/hermesSkills --skill systematic-debugging-karlinskys
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: systematic-debugging
Source: https://github.com/KarlinskyS/hermesSkills/tree/main/software-development/systematic-debugging
Command: npx skills add https://github.com/KarlinskyS/hermesSkills --skill systematic-debugging-karlinskys

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Systematic Debugging provides a disciplined framework to diagnose bugs, test failures, and unexpected behavior by enforcing a four-phase root-cause investigation before implementing fixes.

Core Features & Use Cases

  • Four-phase methodology (Phase 1 Root Cause Investigation, Phase 2 Pattern Analysis, Phase 3 Hypothesis and Testing, Phase 4 Implementation) guiding teams from error observation to validated resolution.
  • Diagnostic instrumentation and evidence gathering guidance: read error messages, reproduce reliably, review recent changes, trace data flow, and compare components.
  • Integration with Hermes agent tools (search_files, read_file, terminal, web_search) and guidance for delegate_task and test-driven development to coordinate multi-component debugging.
  • Applicable to any technical issue (test failures, production bugs, unexpected behavior) and suited for high-stress emergencies where a quick patch may seem tempting but is avoided.

Quick Start

Initiate Phase 1 by reproducing the issue, collecting error data, and tracing data flow, then progress through Phases 2–4 to identify and fix root causes before proposing changes.

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 software bug instead of guessing at fixes?▼

Root-cause debugging enforces a four-phase investigation methodology to stop guesswork. It guides you through error message analysis, reliable reproduction, and data-flow tracing across API, service, and database boundaries before applying any code fixes.

What is the best way to debug multi-component test failures and trace data flow?▼

Tracing data flow for test failures requires systematic diagnostic instrumentation across API and database boundaries. This methodology uses structured error reading and evidence gathering to coordinate multi-component debugging and identify the exact failure origin.

How do I systematically reproduce an unexpected software error before changing code?▼

Systematic reproduction starts with Phase 1 root cause investigation, collecting error data and reading error messages. You must reliably reproduce the issue, review recent changes, and gather diagnostic evidence before progressing to pattern analysis.

Can I use this systematic debugging methodology for production bugs in high-stress emergencies?▼

Yes, the root-cause debugging methodology is suited for high-stress production bug emergencies. It specifically prevents applying quick patches by enforcing evidence gathering, hypothesis testing, and pattern analysis before implementing validated resolutions.

Do I need specific agent tools to perform structured root-cause diagnostics?▼

Structured root-cause diagnostics integrate with the Hermes toolset, utilizing search_files, read_file, terminal, and web_search. These tools enable systematic error-message analysis and data-flow tracing across multi-component systems during the investigation phases.

Why does applying quick patches during multi-component debugging often fail?▼

Applying quick patches fails because it skips the four-phase root-cause investigation, ignoring data-flow tracing and evidence gathering. Systematic debugging prevents this by enforcing pattern analysis and hypothesis testing to validate the true origin before implementation.

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