Agent skill · data analytics · nexscope-ai
price-optimization-tool
Evaluate ecommerce price candidates using unit economics, historical observations, elasticity analysis, scenario modeling, and controlled experiments. Use when a seller asks what price to test, how price changes could affect contribution or revenue, how to estimate elasticity, how to optimize a bundle or tier, or how to design a price experiment across Amazon, Shopify, TikTok Shop, Walmart, eBay, or other channels. Do not claim a proven optimal price without sufficient clean data, and do not change live prices without explicit authorization.
Why this skill is useful
Provides domain-specific knowledge on price elasticity estimation and controlled pricing experiments that the AI wouldn't reliably generate on its own.
What it needs
Requires nexscope-ai/ecommerce-skills installed locally. About 7k tokens when loaded. Last updated 2026-07-23. 604 stars on the source repository.
What this skill does
Price Optimization Tool Build an evidence-bounded price decision from seller economics and observed behavior, then recommend a reversible test or rollout with explicit uncertainty. Installation Capabilities Audit price, demand, traffic, promotion, cost, and inventory data for comparability. Calculate contribution economics and hard candidate-price constraints. Estimate directional or numeric elasticity only when the evidence supports it. Compare price candidates under base, downside, and upside demand scenarios. Optimize regular, promotional, bundle, quantity, and good-better-best price candidates. Design controlled price tests with hypotheses, guardrails, confounder controls, and decision rules. Produce a recommendation with uncertainty, approval requirements, and a reversible rollout. Usage Examples Inputs and Collection Use seller-supplied and inspected evidence first. Collect: SKU, variant, channel, market, currency, tax treatment, fulfillment method, lifecycle stage, and business objective; timestamped regular price, realized selling price, list or compare-at price, coupons, promotions, and seller-funded discounts; timestamped sessions or impressions, orders, units, net revenue, cancellations, returns, and inventory availability; COGS, inbound freight, duties, packaging, fulfillment, payment, referral, affiliate, ad, return, and other variable costs; traffic source, ad spend, content or listing changes, stock status, seasonality, events, and promotion windows; comparable competitor offers with source, capture time, variant, pack size, availability, shipping, seller, and fulfillment; bundle components, attach rates, cannibalization risks, tier thresholds, and operational constraints; target metric, approved floor and ceiling, test duration constraints, platform rules, approver, and risk tolerance. If material inputs are missing, ask one consolidated follow-up. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills nexscope-ai/price-optimization-tool