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systematic-debugging

Identify and fix defects in scientific code using a four-phase debugging workflow.

1|1|Updated Jan 23, 2026
Search Tags:#debugging#logging#reproducibility#root-cause#research-code
One-click install
npx skills add https://github.com/Hollis36/claude-skill --skill systematic-debugging-hollis36
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: systematic-debugging
Source: https://github.com/Hollis36/claude-skill/tree/main/systematic-debugging
Command: npx skills add https://github.com/Hollis36/claude-skill --skill systematic-debugging-hollis36

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Identify and fix defects in scientific code using a structured four-phase debugging workflow.

Core Features & Use Cases

  • Structured four-phase workflow: reproduce, locate, diagnose, and fix with guardrails.
  • Root-cause analysis templates and logging strategies to isolate issues.
  • Defensive programming guidance and troubleshooting templates for reproducible research.

Quick Start

Describe a reproducible debugging task in plain language for the AI to execute immediately.

Frequently Asked Questions about systematic-debugging

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

FAQPage Schema
How do I debug scientific research code systematically?▼

Debug scientific research code by applying a structured four-phase workflow to reproduce, locate, diagnose, and fix defects with guardrails. Root-cause analysis templates and logging strategies isolate issues, while defensive programming ensures reproducible steps and verifiable fixes.

What is the best way to ensure reproducibility when troubleshooting data analysis scripts?▼

Ensure reproducibility in data analysis scripts by enforcing repeatability through structured logging and defensive coding. The workflow isolates root-causes with tracking templates, preventing recurring defects and verifying that fixes do not break experimental pipelines.

How do I find the root-cause of defects in simulation models?▼

Find the root-cause of defects in simulation models by applying structured analysis templates and logging strategies within a diagnostic phase. This isolates issues across experimental pipelines and ensures fixes are verifiable through defensive programming.

Can I apply a structured debugging workflow to experimental pipelines?▼

Yes, you can apply a structured debugging workflow to experimental pipelines. The four-phase approach handles data analysis scripts and simulation models, utilizing reproducible steps and root-cause tracking to identify and fix defects with verifiable guardrails.

Why does my research code keep having non-repeatable defects?▼

Research code has non-repeatable defects when it lacks enforced repeatability and defensive coding. Implementing a structured workflow with logging strategies and root-cause tracking templates isolates issues and establishes verifiable fixes across experimental pipelines.

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