diagnose

Diagnose software bugs through structured hypothesis generation and evidence collection.

113|15|Updated Mar 3, 2026

Search Tags:#debugging #diagnose #root-cause #incident-management #hypothesis-testing #runtime-instrumentation

Ready to run

npx skills add https://github.com/avibebuilder/claude-prime --skill diagnose-avibebuilder

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: diagnose
Source: https://github.com/avibebuilder/claude-prime/tree/main/.claude/skills/diagnose
Command: npx skills add https://github.com/avibebuilder/claude-prime --skill diagnose-avibebuilder

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

Investigate and diagnose unexpected software bugs and mysterious behavior by following a structured, hypothesis-driven workflow that isolates root causes without rewriting user prompts or forcing fixes.

Core Features & Use Cases

Symptom understanding: Clarify and document visible symptoms to separate facts from assumptions.
Hypothesis generation: Produce multiple, distinct root-cause hypotheses and assess their plausibility.
Evidence-guided testing: Plan and gather minimal, safe runtime evidence to validate or falsify hypotheses.
Diagnosis output: Produce a clear, structured diagnosis with supporting evidence and next steps for remediation.

Quick Start

Describe the observed symptoms, generate hypotheses, and instrument minimally to test them.

Frequently Asked Questions about diagnose

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 that is hard to reproduce?▼

To find the root cause of a hard-to-reproduce software bug, use a structured, hypothesis-driven workflow that separates facts from assumptions, generates multiple root-cause hypotheses, and gathers minimal runtime evidence to validate them.

What is hypothesis-driven debugging and when should I use it for incident management?▼

Hypothesis-driven debugging is a structured approach that generates distinct root-cause hypotheses and tests them with minimal runtime instrumentation. Use it for incident management when symptoms are unclear, reproducibility is hard, or the root cause is unknown.

How do I systematically diagnose unexpected behavior in software systems without applying fixes?▼

Systematically diagnose unexpected behavior by following a workflow of symptom understanding, hypothesis creation, and evidence-guided testing. This process isolates the root cause and outputs a formal diagnosis without performing fixes or rewriting code.

Can I use runtime instrumentation to test root cause hypotheses during an incident?▼

Yes, you can plan and apply minimal, safe runtime instrumentation to gather evidence that validates or falsifies specific root-cause hypotheses during an incident. This ensures you confirm the diagnosis with data before attempting remediation.

What is the best way to investigate unclear symptoms during software incident management?▼

The best way to investigate unclear symptoms is to first clarify and document visible facts to separate them from assumptions. This symptom understanding phase prevents premature fixes and grounds the subsequent root-cause hypothesis generation in observed evidence.

Why does my debugging process fail to identify the correct root cause of mysterious behavior?▼

Debugging fails to identify the root cause of mysterious behavior when it skips structured fact-finding and relies on assumptions. A formal diagnosis requires generating multiple hypotheses and collecting supporting runtime evidence to validate them before concluding.