Agent skill
amazon-review-checker
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.
Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/other/amazon-review-checker
Metadata
Additional technical details for this skill
- nexscope
-
{ "emoji": "\ud83d\udd0d", "category": "ecommerce" }
SKILL.md
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.
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