ecommerce.review-monitor

IMPORTANT — Working Directory: All scripts in this skill MUST be executed with the working directory set to the absolute path of the directory containing this SKILL.md file (the skill root directory). Always cd into this directory before running any command. Do NOT use relative paths or shell shortcuts like ~ in paths, as they may not be resolved by the execution environment.

Review Monitor v1.0.0

Core Question

What new or recent review changes should the seller react to?

What do new reviews say?

Clarify or Infer Before Querying

• If ASIN is missing, ask for it or resolve it from product search.
• Clarify marketplace, monitoring window, and whether the user cares about negative reviews, sentiment, rating shifts, or topics.
• Do not substitute deep historical review mining unless the user asks for pain points.

When to Use

• User wants to check recent reviews
• User asks "what are customers saying"
• User wants to monitor review sentiment
• User needs alerts on negative reviews
• User asks about review trends

Differs From / Not Applicable

• Use review-checker for deep review mining and complaint themes.
• Use product-validator for review authenticity as part of full ASIN validation.
• Use this skill for recent review changes, alerts, and sentiment tracking.

Difference from review-checker

Feature	review-checker	review-monitor
Focus	Pain point mining	Recent review monitoring
Purpose	Product research	Ongoing monitoring
Analysis	Deep pain point extraction	Sentiment + topic analysis
Use case	Before entering market	After product launch

Data Sources

Source	Endpoint	Data
NexScope Proxy	/api/v1/tools/research/amazon/reviews/list	Reviews for non-US markets
NexScope Proxy	/api/v1/tools/research/amazon/usReviewsList	Reviews for US market

Supported Marketplaces

Market	Domain	Status
UK, CA, DE, FR, JP, AU, IN	Direct	Supported
US	-	Supported (via /api/v1/tools/research/amazon/usReviewsList)

MANDATORY: Charts & Display Rules

1. Generate charts by default for full analytical reports - use --chart with an output directory unless the user asks for a quick text-only result or chart data is unavailable.
2. Send generated charts to the user - when charts are created, share all chart PNGs immediately.
3. All chart styling is driven by ecommerce_chart_helpers.py which reads from chart_style.json (derived from references/display-rules.md). Do NOT hardcode colors in scripts.

Usage

# Basic monitoring
python3 scripts/review_monitor.py '{"asin": "B0BTYCRJSS"}'

# Specific market
python3 scripts/review_monitor.py '{"asin": "B0BTYCRJSS", "market": "UK"}'

# More reviews per star
python3 scripts/review_monitor.py '{"asin": "B0BTYCRJSS", "count_per_star": 30}'

# With charts
python3 scripts/review_monitor.py '{"asin": "B0BTYCRJSS"}' --chart /tmp/charts

Parameters

Parameter	Type	Required	Default	Description
asin	string	Yes	-	ASIN to monitor
market	string	No		Marketplace
count_per_star	int	No	20	Reviews per star rating (max 100)

Output Structure

The output will be a structured markdown report, following this format:

Review Monitoring Report: [ASIN]

---

1. Executive Summary

• Monitored ASIN: [asin]
• Monitored Market: [market]
• Total Reviews Analyzed: [total_reviews]
• Current Product Rating: [product_rating]
• Average Recent Review Rating: [analysis.average_rating]
• Key Insight: This report monitors recent reviews, analyzes sentiment, and highlights key trends and alerts.

2. Review Analysis Overview

• Total Reviews: [analysis.total_analyzed]
• Average Rating: [analysis.average_rating]
• Verified Review Percentage: [analysis.verified_percentage]%
• Negative Review Percentage: [analysis.negative_percentage]%
• Current Status: [insights.status]

3. Rating Distribution

• Star Rating Distribution:

Star Rating	Review Count	Share (%)
1 Star	[analysis.rating_distribution.1]	[calculated percentage]%
2 Stars	[analysis.rating_distribution.2]	[calculated percentage]%
3 Stars	[analysis.rating_distribution.3]	[calculated percentage]%
4 Stars	[analysis.rating_distribution.4]	[calculated percentage]%
5 Stars	[analysis.rating_distribution.5]	[calculated percentage]%

4. Sentiment Distribution

• Review Sentiment Distribution:

Sentiment	Review Count	Share (%)
Positive	[analysis.sentiment_distribution.positive]	[calculated percentage]%
Negative	[analysis.sentiment_distribution.negative]	[calculated percentage]%
Mixed	[analysis.sentiment_distribution.mixed]	[calculated percentage]%
Neutral	[analysis.sentiment_distribution.neutral]	[calculated percentage]%

5. Top Topics

• Most frequently mentioned topics in reviews:

Topic	Mention Count
[analysis.topic_frequency.topic1]	[analysis.topic_frequency.topic1_count]
[analysis.topic_frequency.topic2]	[analysis.topic_frequency.topic2_count]
[analysis.topic_frequency.topic3]	[analysis.topic_frequency.topic3_count]
...	...

6. Alerts Found

• Alert List:

Type	Severity	Icon	Message
[alerts[0].type]	[alerts[0].severity]	[alerts[0].icon]	[alerts[0].message]
...	...	...	...

7. Key Findings & Recommendations

• Key Findings:
  • [insights.key_findings[0]]
  • [insights.key_findings[1]]
  • ...
• Recommendations: (derived from alerts and key findings)

8. Sample Reviews

• Top Positive Reviews:
  • [sample_reviews.top_positive[0]]
  • ...
• Latest Negative Reviews:
  • [sample_reviews.recent_negative[0]]
  • ...

9. Attached Visualizations

• Rating Distribution (1_rating_distribution.png)
• Sentiment Analysis (2_sentiment.png)
• Common Topics (3_topics.png)
• Alert Distribution (4_alerts.png)

Sentiment Categories

Sentiment	Meaning	Trigger
positive	Happy customer	Rating >=4 or positive keywords
negative	Unhappy customer	Rating <=2 or negative keywords
mixed	Mixed feelings	Rating 3 or conflicting signals
neutral	Factual review	No strong sentiment detected

Topics Tracked

Topic	Example Keywords
quality	quality, well made, cheap, flimsy
price_value	price, value, worth, expensive
shipping	shipping, delivery, package, damaged
functionality	works, function, performance
durability	lasted, durable, broke, stopped working
size_fit	size, fit, small, big, tight
appearance	looks, color, design, beautiful
ease_of_use	easy, simple, difficult, setup
customer_service	customer service, return, refund

Alert Types

Alert	Severity	Trigger
High Negative	HIGH	>=30% negative reviews
Moderate Negative	MEDIUM	15-30% negative reviews
Low Rating	HIGH	Average rating < 3.5
One-Star Reviews	HIGH	Any 1-star reviews found
Topic Issue	MEDIUM	3+ complaints on same topic

Charts Generated

Chart	Description	File
Rating Distribution	Bar chart by stars	1_rating_distribution.png
Sentiment Analysis	Positive/Negative/Mixed	2_sentiment.png
Common Topics	Horizontal bar chart	3_topics.png
Alerts	Alert severity breakdown	4_alerts.png

Workflow Integration

Product Monitoring
|-- price-monitor -> Track prices
|-- review-monitor -> Monitor reviews -> YOU ARE HERE
|-- keyword-rank-tracker -> Track rankings
`-- competitor-analyzer -> Watch competitors

Example Report

ASIN: B0BTYCRJSS | 100 Reviews Analyzed

Metric	Value
Average Rating	3.8 stars
Positive	55%
Negative	28%
Verified	85%

Top Topics:

1. Quality (35 mentions)
2. Price/Value (28 mentions)
3. Functionality (22 mentions)

Alerts:

• 28% negative reviews - monitor closely
• Quality complaints: 15 mentions

Sample Negative Review:

2/5 stars

Use Cases

1. Daily Review Check

2. Negative Review Alert

3. Topic Analysis

4. Competitor Review Monitor

Limitations

• US market supported via dedicated /api/v1/tools/research/amazon/usReviewsList endpoint
• Max 100 reviews per star rating
• Sentiment analysis is keyword-based (not AI)
• Real-time monitoring not available (manual refresh needed)
• Historical comparison not included (use review-checker for trends)

Environment Variables

Variable	Required	Description
NEXSCOPE_PROXY_BASE	Yes	NexScope proxy base URL
NEXSCOPE_API_KEY	Yes	NexScope proxy API key

References

• references/display-rules.md - Output formatting