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Amazon Review Checker

核心功能:生成0-100的真实性评分,从时间聚类、内容相似度等多维度检测假评论与可疑模式,支持L1-L4四级递进分析(依提供的评论内容、日期、评分、认证状态等数据解锁不同深度)。典型场景:电商卖家排查商品评论可信度。输入支持粘贴评论、JSON格式数据,输出带风险等级的分析报告,标注高风险评论并说明原因,还会给出补充数据的优化建议。

phheng
phheng
热度 47.12
最近更新 2026-05-11 17:34:55
分类:数据依赖:代码执行 / 内部调用大模型应用场景:市场分析 / 报告撰写 / 数据处理

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add amazon-review-checker
Metadata
name
amazon-review-checker
version
1.0.0
description
Amazon review authenticity analyzer. Detect fake reviews, suspicious patterns, and rating manipulation. Includes time clustering detection, content similarity analysis, rating distribution checks, and verified purchase validation. Progressive analysis with L1-L4 depth levels. No API key required.
metadata
{"nexscope":{"emoji":"🔍","category":"ecommerce"}}

Amazon Review Checker 🔍

Review authenticity analyzer — detect fake reviews, suspicious patterns, and rating manipulation.

Installation

npx skills add nexscope-ai/eCommerce-Skills --skill amazon-review-checker -g

Features

  • Authenticity Score — 0-100 comprehensive rating
  • Suspicious Pattern Detection — Time clustering, content similarity, rating anomalies
  • Fake Review Flagging — Mark high-risk reviews with explanations
  • Progressive Analysis — More data = deeper insights

Progressive Analysis Levels

Level Required Data Unlocked Analysis
L1 Basic Review content Similarity, length, keywords
L2 Advanced + Review date Time clustering detection
L3 Deep + Star rating Rating distribution analysis
L4 Complete + VP status Verified purchase validation

Detection Dimensions

Dimension Weight Method
Time Clustering 25% Sliding window + burst detection
Content Similarity 20% N-gram + Jaccard similarity
Rating Distribution 20% Chi-square test vs natural distribution
VP Ratio 15% Compare to category benchmark
Review Length 5% Entropy analysis
Suspicious Keywords 5% Keyword pattern matching

Risk Levels

Score Level Description
70-100 ✅ Low Risk Reviews appear authentic
50-69 ⚠️ Medium Risk Some concerns found
30-49 🔴 High Risk Multiple red flags
0-29 💀 Critical Likely mass fake reviews

Usage

Method 1: Paste Reviews

Paste reviews directly in conversation:

Check these reviews:

5 stars - Great product! Works perfectly.
5 stars - Amazing! Best purchase ever.
1 star - Not as described.

Method 2: JSON Input

python3 scripts/analyzer.py '[
  {"content": "Great product!", "rating": 5, "date": "2024-01-15", "verified_purchase": true},
  {"content": "Amazing!", "rating": 5, "date": "2024-01-15", "verified_purchase": false}
]'

Method 3: Demo Mode

python3 scripts/analyzer.py --demo

Output Example

📊 Review Authenticity Report

ASIN: B08XXXXX
Reviews: 10
Analysis Level: L4

━━━━━━━━━━━━━━━━━━━━━━━━

Authenticity Score: 66/100 ⚠️

Medium Risk - Some concerns found.

━━━━━━━━━━━━━━━━━━━━━━━━

Detection Dimensions

🔴 Time Clustering: 70/100
   Max 6 reviews within 48h

✅ Content Similarity: 24/100
   Found 0 highly similar review groups

━━━━━━━━━━━━━━━━━━━━━━━━

High-Risk Reviews (Top 3)

1. Risk 75% - "Perfect!"
   Reason: Too short, non-VP, templated 5-star

🔍 Want more accurate analysis? Add:
• Reviewer info → Unlock "Account Profile Analysis"

Interaction Flow

User Input (any format)
        ↓
Smart field detection
        ↓
Analyze with available data
        ↓
Results + depth suggestions
        ↓
User continues or ends

Part of Nexscope AI — AI tools for e-commerce sellers.