A powerful tool for optimizing product pricing through data-driven elasticity analysis and competitor benchmarking.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install price-optimization-tool
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install price-optimization-tool using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
The Price Optimization Tool is a professional-grade solution designed for e-commerce sellers and developers looking to maximize revenue and profit. By leveraging data-driven methods, this skill allows users to perform complex tasks like price elasticity estimation and margin modeling directly within their AI agent environment. It integrates seamlessly with Openclaw Skills to provide actionable insights across various marketplaces, ensuring that every pricing decision is backed by statistical significance.
This skill bridges the gap between raw sales data and strategic pricing decisions. Whether you are managing a single SKU or a large catalog, the tool helps maintain cross-marketplace price harmonization and promotional planning. It simplifies the process of setting up price monitoring alerts and ensuring your margins remain healthy after accounting for platform fees and logistics costs.
To begin using this tool, install it via the command line within your project directory:
npx skills add nexscope/price-optimization-tool
Once installed, you can configure your product cost data and competitor URLs to allow the AI to perform accurate benchmarking. The skill works best when provided with detailed fee structures for specific marketplaces like Amazon, Shopify, or eBay.
The Price Optimization Tool organizes data into structured objects for easy analysis and reporting. This schema ensures that Openclaw Skills can process and output pricing data consistently.
| Entity | Description | Key Fields |
|---|---|---|
| Product Profile | Core data for optimization | SKU, Cost, Current Price, Platform Fees |
| Competitor Map | Benchmarking data | URL, Competitor Price, Rating, Stock Status |
| Testing Plan | A/B testing parameters | Duration, Sample Size, Variant Prices, Significance |
| Margin Model | Financial breakdown | Net Profit, ROI, Contribution Margin |
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