root-cause-analyzer
Systematic root cause identification skill with 5 Whys, fishbone diagrams, fault tree analysis, and hypothesis testing
Best use case
root-cause-analyzer is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Systematic root cause identification skill with 5 Whys, fishbone diagrams, fault tree analysis, and hypothesis testing
Teams using root-cause-analyzer should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/root-cause-analyzer/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How root-cause-analyzer Compares
| Feature / Agent | root-cause-analyzer | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Systematic root cause identification skill with 5 Whys, fishbone diagrams, fault tree analysis, and hypothesis testing
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Root Cause Analyzer
## Overview
The Root Cause Analyzer skill provides comprehensive capabilities for systematic root cause identification and verification. It supports multiple analysis methods including 5 Whys, Ishikawa diagrams, fault tree analysis, and statistical hypothesis testing.
## Capabilities
- 5 Whys facilitation
- Ishikawa (fishbone) diagram creation
- Fault tree analysis (FTA)
- Hypothesis formulation
- Chi-square testing
- Correlation analysis
- Pareto chart generation
- Root cause verification
## Used By Processes
- SIX-005: Root Cause Analysis
- QMS-005: FMEA Facilitation
- CI-002: A3 Problem Solving
## Tools and Libraries
- Cause analysis tools
- Statistical testing libraries
- Visualization platforms
- Collaboration tools
## Usage
```yaml
skill: root-cause-analyzer
inputs:
problem_statement: "25% increase in customer complaints for product X"
analysis_method: "fishbone" # 5_whys | fishbone | fta | is_is_not
data:
defect_counts_by_category:
materials: 45
methods: 23
machines: 67
manpower: 12
measurement: 8
environment: 5
hypothesis_to_test: "Machine wear is causing increased defects"
outputs:
- root_cause_diagram
- potential_causes
- verified_root_causes
- pareto_analysis
- statistical_verification
- recommendations
```
## Analysis Methods
### 5 Whys
Ask "Why?" iteratively to drill down to root cause:
1. Why did the problem occur?
2. Why did that happen?
3. Why did that happen?
4. Why did that happen?
5. Why did that happen?
### Ishikawa (Fishbone) Categories
- **Man** (Manpower) - Training, skills, fatigue
- **Machine** - Equipment, tools, technology
- **Method** - Procedures, processes, policies
- **Material** - Raw materials, consumables
- **Measurement** - Inspection, calibration
- **Mother Nature** (Environment) - Temperature, humidity, conditions
### Fault Tree Analysis
- Top event (undesired outcome)
- AND gates (all inputs required)
- OR gates (any input sufficient)
- Basic events (root causes)
## Verification Techniques
| Technique | Use Case |
|-----------|----------|
| Chi-square test | Categorical data relationships |
| Correlation analysis | Continuous variable relationships |
| Regression | Predictive relationships |
| Designed experiments | Controlled cause-effect testing |
| Pareto analysis | Vital few vs. trivial many |
## Integration Points
- Quality Management Systems
- Corrective action systems
- Statistical analysis tools
- Knowledge management systemsRelated Skills
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