liangdabiao

liangdabiao / simple-review-analyzer

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AI驱动的电商产品评论深度分析工具，支持22维度智能标签、用户画像识别、VOC洞察和可视化看板生成。适合用于Claude Code CLI /openclaw 等工具。同时展示怎样制作一个直接skill (openclaw / claude code 等），不依赖其他， 对电商评论进行深度数据分析，

linux.dottopic1789421 agent
13
1
100% credibility
Found Mar 24, 2026 at 13 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
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AI Summary

AI tool that deeply analyzes e-commerce product reviews by applying 22 intelligent tags across user demographics, quality, service, and more, then generates labeled data files, insights reports, and interactive visualization dashboards.

How It Works

1
📦 Gather customer reviews

Collect feedback from your online store shoppers into one simple file like a spreadsheet.

2
💬 Ask your AI helper

Chat with your smart AI assistant and say something like 'analyze these product reviews for me' while pointing to your file.

3
Pick your analysis depth
⚡
Quick scan

Look at the latest 100 reviews for fast key takeaways.

🔍
Deep dive

Examine all reviews to uncover every detail and trend.

4
✨ Smart labeling magic

Your AI reads each review and adds clever labels about buyer types, usage scenes, quality feels, service gripes, and loves across 22 smart categories.

5
📋 Get your organized results

Receive an updated file with all labels, a story-like insights report, and a colorful interactive webpage full of charts.

🎉 Boost your product

Spot pain points, celebrate wins, understand customers deeply, and plan smart improvements to delight more shoppers.

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AI-Generated Review

What is simple-review-analyzer?

This is a simple review analyzer for e-commerce product comments, powered by Claude via Code CLI or openclaw. Drop in a CSV of reviews (with content and rating columns), and it applies AI to tag them across 22 dimensions like user demographics, quality issues, service complaints, and repurchase intent, while spotting personas and VOC insights. You get three outputs: a tagged CSV, a Markdown report with recommendations, and an interactive HTML dashboard with charts—all invoked via natural language prompts like "analyze these 100 reviews."

Why is it gaining traction?

It stands out by bundling deep analysis into a lightweight openclaw skill—no heavy ML setup, just Claude CLI commands for batch processing up to 100 reviews. Developers dig the zero-config fuzzy column matching for messy CSVs and the pro-grade HTML viz that's responsive and print-ready, skipping the hassle of custom dashboards. The 22-tag system covers real e-commerce pain points comprehensively, making competitor review scans or product optimization instant.

Who should use this?

E-commerce product managers auditing their own reviews for pain points and opportunities. Marketers doing quick competitor analysis on Amazon scrapes to build user personas. Indie devs or analysts prototyping VOC tools without spinning up full pipelines.

Verdict

Grab it if you're in the Claude Code CLI or openclaw ecosystem—solid for targeted review analysis, with clear English docs and MIT license. At 13 stars and 1.0% credibility score, it's early-stage and unproven at scale, so test on small batches first before production reliance.

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