Agent skill · Business & Finance

dynamic-pricing-ecommerce

Design a controlled dynamic-pricing or repricing system for ecommerce products. Use when a seller asks for demand-based, inventory-based, competitor-responsive, or time-based price rules; SKU eligibility; price floors and ceilings; automation approvals; simulations; monitoring; or rollback plans across Amazon, Shopify, TikTok Shop, Walmart, eBay, or other channels. Do not use for a one-time optimal-price calculation or to change live prices without explicit authorization.

nexscope-aigithub.com/nexscope-aiGitHub ↗
claude-codeMIT
Install
npx skills add nexscope-ai/eCommerce-Skills --skill dynamic-pricing-ecommerce --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 13 KB
Bundled scripts: none
Path: dynamic-pricing-ecommerce/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 580
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Dynamic Pricing for Ecommerce Turn seller-approved economics and trusted signals into a bounded repricing system with explicit rules, approvals, monitoring, and a kill switch. ## Installation ```bash npx skills add nexscope-ai/eCommerce-Skills --skill dynamic-pricing-ecommerce -g ``` ## Capabilities - Define SKU eligibility for automatic, approval-required, or manual repricing. - Calculate contribution-safe floors and commercially justified ceilings. - Select demand, inventory, competitor, season, and promotion signals without treating noisy observations as facts. - Create deterministic rule matrices with bounded price steps, cooldowns, and conflict precedence. - Simulate normal, downside, promotion-stack, stockout, and price-war scenarios. - Design approval, audit-log, rollback, anomaly-breaker, and emergency-stop controls. - Produce a staged platform implementation and measurement plan without enabling live changes. ## Usage Examples ```text Design safe Amazon repricing rules for these 200 SKUs without starting a price war. ``` ```text Create an inventory-aware dynamic pricing plan for my Shopify store. ``` ```text Which products can be auto-repriced, and which should always re

What's inside
Steps it walks through
  1. Installation
  2. Capabilities
  3. Usage Examples
  4. Inputs and Collection
  5. Workflow
  6. 1. Establish the Evidence Boundary
  7. 2. Calculate Economic Guardrails
  8. 3. Classify SKU Automation Eligibility
  9. 4. Select and Validate Signals
  10. 5. Build the Rule Matrix
  11. 6. Simulate Before Enabling
  12. 7. Design Governance and Rollback
  13. 8. Stage the Rollout and Measurement
  14. Domain Rules
Ships with 1 file
  • agents/openai.yaml
Commands it runs
npx skills add nexscope-ai/eCommerce-Skills --skill dynamic-pricing-ecommerce -g
More from eCommerce-Skills
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About this skill
What does the dynamic-pricing-ecommerce skill do?

Design a controlled dynamic-pricing or repricing system for ecommerce products. Use when a seller asks for demand-based, inventory-based, competitor-responsive, or time-based price rules; SKU eligibility; price floors and ceilings; automation approvals; simulations; monitoring; or rollback plans across Amazon, Shopify, TikTok Shop, Walmart, eBay, or other channels. Do not use for a one-time optimal-price calculation or to change live prices without explicit authorization.

How do I install it?

Run `npx skills add nexscope-ai/eCommerce-Skills --skill dynamic-pricing-ecommerce --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From nexscope-ai/eCommerce-Skills, a repository with 580 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going