diagnosing

Diagnose software errors by gathering evidence and testing hypotheses.

1|Updated Jan 31, 2026

Search Tags:#debugging #root cause #troubleshooting #error analysis #hypothesis testing #evidence gathering

Ready to run

npx skills add https://github.com/jugrajsingh/skillgarden --skill diagnosing

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: diagnosing
Source: https://github.com/jugrajsingh/skillgarden/tree/main/plugins/unstuck/skills/diagnosing
Command: npx skills add https://github.com/jugrajsingh/skillgarden --skill diagnosing

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps systematically investigate the root cause of errors by gathering evidence, forming hypotheses, and testing them, preventing wasted time on incorrect assumptions.

Core Features & Use Cases

Systematic Investigation: Guides users through a structured process to identify the origin of bugs.
Evidence Gathering: Collects critical information like error messages, stack traces, and recent code changes.
Hypothesis Testing: Facilitates the formulation and minimal testing of specific, actionable hypotheses.
Use Case: When a feature suddenly breaks, this Skill helps pinpoint whether a recent code change, an unexpected input, or a configuration issue is the culprit.

Quick Start

Use the diagnosing skill to investigate the error that occurred during the last deployment.

Frequently Asked Questions about diagnosing

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

FAQPage Schema

How do I perform root cause analysis for a software bug?▼

Root cause analysis for software bugs requires systematically gathering evidence like error messages and stack traces, forming testable hypotheses, and running minimal tests to pinpoint the origin. This structured investigation prevents wasted time on incorrect assumptions.

What is the best way to troubleshoot an error when the source is unclear?▼

Troubleshooting unclear errors involves collecting critical information such as recent code changes and unexpected inputs, then guiding minimal testing to validate specific hypotheses. This systematic approach identifies whether configuration issues or code changes are the culprit.

How do I systematically debug an issue that suddenly breaks a feature?▼

To systematically debug a broken feature, gather evidence by reading error messages and reproducing the issue. Formulate actionable hypotheses about recent code changes or inputs, then test them minimally to isolate the root cause.

Can I use hypothesis testing to investigate errors from my last deployment?▼

Hypothesis testing can investigate deployment errors by analyzing code changes and gathering evidence to form specific, actionable assumptions. By validating these hypotheses through minimal testing, you can identify if the deployment introduced the bug.

When should I use a structured investigation process for debugging?▼

A structured investigation process for debugging should be used when the source of a bug is unclear and you need to prevent wasted time on incorrect assumptions. It guides you through evidence gathering and hypothesis testing for accurate root cause analysis.

What evidence do I need to gather for effective error analysis?▼

Effective error analysis requires gathering critical information like error messages, stack traces, and recent code changes. This evidence forms the basis for creating testable hypotheses to identify the root cause of software bugs.