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investigate

Guide root-cause debugging through investigation, analysis, hypothesis, and implementation phases.

9|1|Updated Apr 16, 2026
Search Tags:#debugging#triage#root-cause#log-analysis#bug-investigation#code-reading
One-click install
npx skills add https://github.com/CarbeneAI/Forge --skill investigate-carbeneai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: investigate
Source: https://github.com/CarbeneAI/Forge/tree/main/.claude/skills/investigate
Command: npx skills add https://github.com/CarbeneAI/Forge --skill investigate-carbeneai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Systematic debugging helps teams identify the true root cause of bugs quickly by guiding through collection, analysis, hypothesis, and implementation phases.

Core Features & Use Cases

  • Phase-driven workflow: investigate, analyze, hypothesize, and implement with clear guardrails to avoid fixing symptoms.
  • Evidence gathering: collect symptoms, read code, review git history, and reproduce the issue to validate root causes.
  • Interactive context handling: prompts for one-question-at-a-time clarifications when context is missing.

Quick Start

Begin a root-cause debugging workflow for a bug by gathering symptoms, reading code, and forming a hypothesis.

Frequently Asked Questions about investigate

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

FAQPage Schema
What is root-cause debugging and how does it prevent recurring software bugs?▼

Root-cause debugging identifies the true origin of software bugs through systematic investigation, analysis, and hypothesis validation. It enforces an Iron Law: no fixes without root cause, preventing teams from patching symptoms and causing recurring bugs.

How do I debug a crash across multiple services using a systematic workflow?▼

Debug a crash using a four-phase workflow: investigate symptoms, analyze evidence, hypothesize root causes, and implement fixes. It relies on standard tools like grep and code reading to gather evidence, review git history, and reproduce the issue.

Can I use this root-cause investigation approach for large-scale codebases and deployments?▼

Yes, root-cause debugging at scale handles errors, crashes, and unexpected behavior across large codebases, services, or deployments. It systematically guides investigation and evidence gathering to validate root causes before implementing fixes.

What is the best way to triage unexpected behavior when initial context is missing?▼

Triage unexpected behavior with interactive context handling that prompts one-question-at-a-time clarifications when context is missing. It gathers symptoms, reads code, and reviews git history to form a validated root-cause hypothesis.

Why does fixing software bug symptoms without a root cause hypothesis lead to failed deployments?▼

Fixing symptoms without a root cause hypothesis violates the Iron Law of systematic debugging, meaning the underlying issue remains. Evidence collection and hypothesis validation are required to ensure fixes address the true origin of unexpected behavior.

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