abc-xyz-classifier
Multi-dimensional inventory classification skill combining value (ABC) and demand variability (XYZ) analysis for differentiated policies
Best use case
abc-xyz-classifier is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Multi-dimensional inventory classification skill combining value (ABC) and demand variability (XYZ) analysis for differentiated policies
Teams using abc-xyz-classifier 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/abc-xyz-classifier/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How abc-xyz-classifier Compares
| Feature / Agent | abc-xyz-classifier | 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?
Multi-dimensional inventory classification skill combining value (ABC) and demand variability (XYZ) analysis for differentiated policies
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
# ABC-XYZ Classifier
## Overview
The ABC-XYZ Classifier is a multi-dimensional inventory classification skill that combines value-based (ABC) and demand variability (XYZ) analysis to enable differentiated inventory policies. It automates Pareto analysis and demand pattern classification to recommend optimal stocking strategies, service levels, and review frequencies.
## Capabilities
- **Pareto Analysis Automation**: Automatically classify inventory into A, B, C categories based on value contribution using Pareto principles
- **Demand Pattern Classification**: Analyze demand variability to classify items as X (stable), Y (variable), or Z (erratic)
- **Inventory Policy Recommendation**: Recommend appropriate inventory policies based on combined ABC-XYZ classification
- **Service Level Differentiation**: Suggest differentiated service level targets based on item classification and business importance
- **Review Frequency Optimization**: Determine optimal inventory review frequencies for each classification
- **Stocking Strategy Suggestions**: Recommend make-to-stock, make-to-order, or hybrid strategies based on classification
- **Cross-Docking Candidacy Identification**: Identify items suitable for cross-docking based on velocity and predictability
## Tools and Libraries
- Statistical Analysis Libraries (pandas, numpy)
- Inventory Optimization Models
- Data Visualization Libraries
- Classification Algorithms
## Used By Processes
- ABC-XYZ Analysis
- Reorder Point Calculation
- Dead Stock and Excess Inventory Management
## Usage
```yaml
skill: abc-xyz-classifier
inputs:
inventory_data:
- sku: "SKU001"
annual_value: 150000
monthly_demand: [100, 98, 102, 99, 101, 100, 98, 103, 99, 100, 101, 99]
unit_cost: 125
- sku: "SKU002"
annual_value: 45000
monthly_demand: [50, 75, 30, 60, 45, 80, 35, 55, 70, 40, 65, 50]
unit_cost: 75
classification_parameters:
abc_thresholds:
A: 80 # Top 80% of value
B: 95 # Next 15% of value
xyz_thresholds:
X: 20 # CV < 20%
Y: 50 # CV 20-50%
outputs:
classifications:
- sku: "SKU001"
abc_class: "A"
xyz_class: "X"
combined_class: "AX"
annual_value: 150000
value_rank: 1
cv_percent: 1.8
recommendation:
service_level: 99.5
review_frequency: "daily"
stocking_strategy: "make_to_stock"
safety_stock_method: "statistical"
- sku: "SKU002"
abc_class: "B"
xyz_class: "Y"
combined_class: "BY"
annual_value: 45000
value_rank: 15
cv_percent: 32.5
recommendation:
service_level: 97.0
review_frequency: "weekly"
stocking_strategy: "make_to_stock"
safety_stock_method: "buffer"
summary:
AX_count: 45
AY_count: 30
AZ_count: 25
BX_count: 150
BY_count: 200
BZ_count: 150
```
## Integration Points
- Enterprise Resource Planning (ERP) Systems
- Inventory Management Systems
- Demand Planning Systems
- Warehouse Management Systems (WMS)
- Financial Systems
## Performance Metrics
- Classification accuracy
- Policy compliance rate
- Service level achievement by class
- Inventory investment by class
- Turn rate by classRelated Skills
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