Amazon Review Checker
by @phheng
Amazon review authenticity analyzer. Detect fake reviews, suspicious patterns, and rating manipulation. Includes time clustering detection, content similarit...
clawhub install amazon-review-checkerπ About This Skill
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":"π","category":"ecommerce"}}
Amazon Review Checker π
Review authenticity analyzer β detect fake reviews, suspicious patterns, and rating manipulation.
Installation
npx skills add nexscope-ai/eCommerce-Skills --skill amazon-review-checker -g
Features
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 | β Low Risk | Reviews appear authentic | | 50-69 | β οΈ Medium Risk | Some concerns found | | 30-49 | π΄ High Risk | Multiple red flags | | 0-29 | π 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
π Review Authenticity ReportASIN: B08XXXXX
Reviews: 10
Analysis Level: L4
ββββββββββββββββββββββββ
Authenticity Score: 66/100 β οΈ
Medium Risk - Some concerns found.
ββββββββββββββββββββββββ
Detection Dimensions
π΄ Time Clustering: 70/100
Max 6 reviews within 48h
β
Content Similarity: 24/100
Found 0 highly similar review groups
ββββββββββββββββββββββββ
High-Risk Reviews (Top 3)
1. Risk 75% - "Perfect!"
Reason: Too short, non-VP, templated 5-star
π Want more accurate analysis? Add:
β’ Reviewer info β Unlock "Account Profile Analysis"
Interaction Flow
User Input (any format)
β
Smart field detection
β
Analyze with available data
β
Results + depth suggestions
β
User continues or ends
Part of Nexscope AI β AI tools for e-commerce sellers.
π‘ Examples
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