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Scientific Debugging (QA & Testing)

Automate Python-based debugging workflows covering reproduction through verification.

Updated Dec 9, 2025
Search Tags:#automation#testing#debugging#QA#reproduction#unit-tests#Junie-mode
One-click install
npx skills add https://github.com/PROdotes/Gosling2 --skill scientific-debugging-qa-testing
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: Scientific Debugging (QA & Testing)
Source: https://github.com/PROdotes/Gosling2/tree/main/.agent/skills/scientific-debugging
Command: npx skills add https://github.com/PROdotes/Gosling2 --skill scientific-debugging-qa-testing

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill provides an evidence-based debugging framework (Junie-Mode) to reproduce, diagnose, fix, and verify software bugs in a disciplined, non-interactive workflow.

Core Features & Use Cases

  • Enforces the Constitution of testing: separation of concerns, mirroring tests to src and tests directories, and a strict logging protocol.
  • Phase-driven debugging: reproduce, investigate, surgical fix, verify, and cleanup.
  • Repro-path automation: creates standalone repro scripts and patches iteratively to validate fixes.

Quick Start

Invoke the skill by mentioning Junie-mode or "Debug this" to activate. The framework will reproduce, investigate, patch, verify, and clean up per the Unified Testing Protocol.

Frequently Asked Questions about Scientific Debugging (QA & Testing)

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

FAQPage Schema
How do I automate bug reproduction and root-cause analysis in Python?▼

Automate bug reproduction and root-cause analysis in Python by applying a phase-driven framework that creates standalone repro scripts, enforces test mirroring, and applies surgical fixes with verification.

What is evidence-based debugging and how does it work with unit tests?▼

Evidence-based debugging works by enforcing separation of concerns and strict logging to reproduce, investigate, patch, verify, and clean up bugs within unit tests for safe, auditable, non-interactive workflows.

How do I structure a debugging workflow to avoid side effects in test suites?▼

Structure a debugging workflow to avoid side effects by enforcing test mirroring between source and tests directories, applying non-interactive logging, and following a strict reproduction to cleanup protocol.

Can I use this automated debugging framework for Python-based test suites only?▼

Yes, this automated debugging framework explicitly applies to bug reproduction, surgical fixes, and verification within Python-based test suites to ensure safe and auditable outcomes.

What's the best way to verify software fixes without interactive debugging?▼

The best way to verify software fixes without interactive debugging is using a phase-driven workflow that patches repro scripts iteratively and enforces non-interactive logging for safe, auditable verification.

Why does my bug reproduction fail when using automated testing workflows?▼

Bug reproduction fails when automated testing workflows lack separation of concerns, proper test mirroring, or strict logging protocols, which this framework enforces through its phase-driven approach.

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