An AI-powered analytical tool that transforms store distribution data into optimized warehousing, distribution, and trunk line transportation strategies.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install warehouse-network-analysis
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install warehouse-network-analysis using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Warehouse Network Analysis Skill?
The Warehouse Network Analysis skill is a technical solution designed for enterprise logistics optimization within the Openclaw Skills framework. It enables developers and supply chain analysts to process store location data and existing delivery infrastructure to generate a comprehensive network blueprint. By calculating spatial coordinates and delivery distances, the skill helps determine where to build warehouses, how to allocate delivery routes, and how to manage inventory transfers effectively.
This skill leverages a cost-minimization methodology, balancing warehousing operations, trunk transportation, and last-mile delivery. It accounts for real-world constraints such as lead-time requirements, existing delivery bases, and multi-level network hierarchies (RDC to FSL via TC), providing actionable data support for corporate logistics strategies.
Warehouse Network Analysis Skill Use Cases
- Assessing the feasibility of setting up new warehouses during market expansion.
- Optimizing regional delivery routes to reduce long-haul transportation costs.
- Designing hub-and-spoke distribution networks for multi-level supply chains.
- Determining optimal replenishment and ordering cycles for diverse store clusters.
- Evaluating the cost-benefit of self-built networks versus 3PL outsourcing in low-density areas.
- Planning inter-warehouse trunk line transportation and transfer schedules.
How Warehouse Network Analysis Skill Works
- The user defines constraint parameters including warehouse limits, coverage goals, and required lead times.
- The skill imports store data from Excel files and performs statistical analysis on city and province distributions.
- Using built-in coordinate databases, it calculates geodetic distances between stores and 17 pre-defined delivery bases.
- It identifies optimal Regional Distribution Centers (RDC) based on connectivity and cost-efficiency.
- The skill constructs a logical network hierarchy, determining if routes should be direct or utilize Transfer Centers (TC).
- A multi-sheet Excel report is generated, featuring visualizations, route planning, and suggested delivery frequencies.
Warehouse Network Analysis Skill Setup
To integrate this skill into your workflow using Openclaw Skills, ensure your environment has the necessary data processing libraries.
# Install required Python dependencies
pip install pandas openpyxl
# Prepare your input file
# Ensure your store data is in .xlsx format with columns for City, Province, and Address.
The agent will first ask for your specific optimization constraints before executing the analysis logic.
Warehouse Network Analysis Skill Data Schema & Taxonomy
The skill processes input data and outputs a comprehensive analysis file with the following metadata taxonomy:
| Data Component | Format | Description |
|---|---|---|
| Input Data | .xlsx | Must contain City, Province, and Detailed Address fields. |
| Visualization Sheet | Excel Chart | Includes provincial distribution and warehouse mapping. |
| Matching Base Sheet | Table | Maps each store to its primary Forward Stocking Location (FSL). |
| Route Planning Sheet | Table | Details RDC to FSL paths including Transfer Centers (TC). |
| Trunk Line Plan | Table | Outlines suggested departure dates and transit times between hubs. |
Warehouse Network Analysis Skill Advanced Features
- Hub-and-Spoke Optimization: Automated selection of Transfer Centers to minimize trunk line hops.
- Cost-Constraint Modeling: Focuses on Min(Total Cost) while maintaining specific service coverage targets.
- Intelligent Zone Mapping: Automatically assigns stores to the nearest efficient delivery base (FSL).
- 3PL Logic Integration: Identifies low-density regions where outsourced delivery is more cost-effective.
- Multi-Level Network Hierarchy: Supports complex logistics structures involving RDCs, TCs, and FSLs.
SKILL.md
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