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BayHorseFurnace / r20-glebis-claude-skills-ecommerce

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🛒 E-commerce & Retail skill suite derived from glebis/claude-skills.

44
0
89% credibility
Found May 06, 2026 at 44 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
AI Summary

A specialized collection of 10 commands and 5 multi-step workflows designed for e-commerce and retail users to optimize products, analyze customers, and plan campaigns within their AI chat assistant.

How It Works

1
🛒 Discover the E-commerce Helper

You hear about a handy toolkit that supercharges your AI assistant for running an online store, with tips for products, prices, and customers.

2
📥 Add It to Your AI Chat

With a quick copy-paste, you bring these special skills into your everyday AI conversations, ready to use in seconds.

3
💬 Start Your First Task

In your chat with the AI, you simply type something like 'product copy' and share details about your item.

4
✨ See Magic Results Appear

Beautiful charts, checklists, and ready-to-use suggestions pop up, showing exactly how to improve your product page for more sales.

5
🔄 Tackle Bigger Projects

Chain commands into full plans like launching a new product or running a sales campaign, watching progress update live.

6
📈 Apply Tips and Grow

You copy the personalized advice to your store, fix weak spots, and start seeing happier customers and better orders.

🎉 Your Store Thrives

With optimized listings, smart pricing, and customer flows, your online business picks up speed and sales soar effortlessly.

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AI-Generated Review

What is r20-glebis-claude-skills-ecommerce?

This GitHub repo delivers a suite of 10 commands and 5 multi-step workflows for Claude AI, adapted from glebis/claude-skills to tackle e-commerce retailer challenges like product catalogue tweaks, conversion rate optimization, and inventory forecasts. Instead of generic AI prompts, you slash-command things like `/product-copy` for optimized titles and bullets or `/cro-audit` for funnel analysis, all spitting out structured tables, progress panels, and action checklists. It's language-agnostic Markdown skills that plug into Claude sessions, solving the drudgery of manual retail analytics for online stores.

Why is it gaining traction?

It carves a niche among e-commerce GitHub projects by focusing on retailer workflows—think dynamic pricing from competitor data or cart abandonment sequences—unlike broad Claude skill packs. The consistent UI with severity-sorted findings and real-time progress hooks devs who hate vague AI outputs, delivering prioritized checklists that feel like a CRO consultant. With 44 stars, it's pulling indie hackers building e-commerce GitHub Flutter or Next.js apps who want Claude as a retail co-pilot.

Who should use this?

E-commerce growth leads auditing Amazon listings or running seasonal campaigns via `product-launch` workflows. Indie retailers handling returns analysis or bundle suggestions without a full Laravel/PHP stack. Marketers at e-commerce retailers in Wien or Rozenburg needing quick LTV predictions and review responses.

Verdict

Grab it if you're already in the Claude ecosystem and need e-commerce retailer tools—solid docs and MIT license make it low-risk to test. But with just 44 stars and a 0.9% credibility score, it's early-stage; validate outputs on real data before production reliance.

(178 words)

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