systematic-debugging

Enforce reproduction, root-cause analysis, and failing-test verification before code changes.

1|Updated May 21, 2026
One-click install
npx skills add https://github.com/hiddink-ai/hiddink-harness --skill systematic-debugging-hiddink-ai
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: systematic-debugging
Source: https://github.com/hiddink-ai/hiddink-harness/tree/main/templates/skills/systematic-debugging
Command: npx skills add https://github.com/hiddink-ai/hiddink-harness --skill systematic-debugging-hiddink-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill addresses the common pitfalls of reactive debugging, such as guessing, "while I'm here" refactoring, and failing to address root causes, which often lead to flaky fixes and recurring bugs.

Core Features & Use Cases

  • Hard Gates: Enforces strict requirements like reproduction-first, failing-test-first, and single-hypothesis validation.
  • Blocker Triage: Provides a structured checklist to resolve environment or dependency issues before declaring a task blocked.
  • Advanced Techniques: Includes specialized procedures for detecting retry storms, cascading failures, and connection pool exhaustion.
  • Use Case: Use this when you encounter a persistent bug or test failure to ensure you identify the root cause and implement a fix that is structurally verified.

Quick Start

Apply the systematic debugging skill to investigate the failing test case in the current module by following the defined phases.

Frequently Asked Questions about systematic-debugging

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

FAQPage Schema
What is the best way to debug intermittent test failures and performance regressions in distributed systems?

Systematic debugging enforces reproduction-first, root-cause analysis, and failing-test verification before any code modification. It mandates strict phase-based gates to isolate faults, preventing reactive guessing and structurally verifying fixes for complex software defects across distributed systems.

How do I stop recurring bugs caused by reactive debugging and unverified code changes?

To stop recurring bugs, enforce an evidence-based debugging workflow with hard gates requiring single-hypothesis validation. This approach eliminates "while I'm here" refactoring by ensuring every fix passes a failing test that structurally verifies the root cause is addressed.

How to identify root causes of cascading failures and connection pool exhaustion?

Identify root causes of cascading failures by applying specialized fault isolation procedures. The workflow includes advanced techniques to detect retry storms and connection pool exhaustion, ensuring you structurally verify the root cause through failing-test-first validation before modifying code.

Does this systematic debugging workflow work for resolving environment and dependency blockers?

Yes, this systematic debugging workflow includes structured blocker triage. It provides a comprehensive checklist to systematically resolve environment or dependency issues before declaring a task blocked, ensuring external factors are eliminated before investigating code defects.

When should I not use an evidence-based debugging workflow with strict phase gates?

You should not use strict evidence-based debugging workflows for trivial, immediately visible code corrections. The rigorous hard gates requiring reproduction, single-hypothesis validation, and failing-test verification are designed for persistent bugs, intermittent test failures, and complex fault isolation.