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Amazon Review Monitor
by
Elway Botty
· GitHub ↗
· v1.0.0
· MIT-0
317
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Install in OpenClaw
/install amazon-review-monitor
Description
Monitor Amazon product reviews by ASIN, analyze ratings and sentiment, identify issues, and draft AI-generated seller responses to negative feedback.
README (SKILL.md)
Amazon Review Monitor — Track, Analyze, Respond
Never miss a negative review again. AI-drafted responses included.
Description
Monitor reviews for any ASIN. Tracks rating distribution, analyzes sentiment, identifies negative themes, and drafts professional seller responses. Set up alerts for new negative reviews.
When to Use
- User wants to monitor Amazon product reviews
- User received a negative review and needs a response
- User wants sentiment analysis on their product reviews
- User asks about review trends or customer feedback
Usage
# Analyze reviews for an ASIN
cd \x3Cskill_dir>/scripts && python3 monitor.py B0XXXXXXXXX
# Analyze 5 pages of reviews on UK marketplace
cd \x3Cskill_dir>/scripts && python3 monitor.py B0XXXXXXXXX co.uk 5
What It Does
- Scrapes recent reviews (configurable depth)
- Shows rating distribution (5⭐ to 1⭐ with visual bars)
- Calculates average rating
- Sentiment analysis (positive/negative word detection)
- Identifies top positive and negative themes
- Highlights negative reviews needing responses
- Drafts professional seller responses based on complaint type
Response Templates Cover
- Product freshness/quality issues
- Shipping damage
- Wrong item/expectations mismatch
- General dissatisfaction
No Dependencies
Pure Python 3. No API keys. No pip install needed.
Usage Guidance
This skill appears to do what it says: scrape Amazon review pages, analyze them, and save local reports with draft responses. Before installing/using, consider: (1) scraping risk and ToS — Amazon may block scraping or prohibit automated scraping for certain uses; (2) privacy — review text can contain personally identifiable or sensitive information and will be stored in reports/reviews-<ASIN>.json, so avoid sharing those files publicly; (3) rate limiting — run with conservative page depths and intervals to avoid IP blocking; (4) legal/compliance — the skill does not post responses to Amazon (it only drafts them), so any automated posting would need separate, authorized tooling and credentials; (5) robustness — the HTML parsing is regex-based and brittle; review parsing may break if Amazon changes page structure. If you need posting or scale (many ASINs), prefer an authorized API/paid service or add proper error handling, retry/backoff, and rate-limiting/proxying with clear authorization.
Capability Analysis
Type: OpenClaw Skill
Name: amazon-review-monitor
Version: 1.0.0
The Amazon Review Monitor skill is a legitimate tool designed to scrape and analyze product reviews using standard Python libraries. The script (scripts/monitor.py) uses urllib to fetch public Amazon review pages, performs basic keyword-based sentiment analysis, and saves the results to a local JSON report. There is no evidence of data exfiltration, unauthorized network calls, or malicious instructions in the SKILL.md file.
Capability Assessment
Purpose & Capability
Name/description align with the included monitor.py: it fetches Amazon review pages, parses reviews, analyzes simple sentiment, and drafts reply templates. No unrelated credentials, binaries, or services are requested.
Instruction Scope
SKILL.md instructs running the bundled Python script and describes the outputs. The script only fetches Amazon review pages, parses review text, prints summaries, drafts responses, and writes a local JSON report to a reports/ directory — all within the declared purpose. Note: the script stores scraped review text locally (reports/reviews-<ASIN>.json).
Install Mechanism
No install spec; skill is instruction-only with a single Python script that uses only standard-library modules. No network downloads or third-party package installs are performed by the skill itself.
Credentials
No environment variables, API keys, or config paths are required. The program performs outbound HTTP(S) requests to amazon.<marketplace> which is consistent with its purpose and does not exfiltrate data to unexpected endpoints.
Persistence & Privilege
Skill is not always-enabled and is user-invocable. It creates per-run local report files under a reports/ directory within the repo workspace; it does not modify other skills or system-wide agent settings.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install amazon-review-monitor - After installation, invoke the skill by name or use
/amazon-review-monitor - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release — Monitor and respond to Amazon product reviews with sentiment analysis and auto-drafted responses.
- Scrapes and analyzes reviews for any ASIN with rating distribution and average score.
- Detects sentiment, key negative/positive themes, and highlights reviews needing attention.
- Generates professional seller response drafts for common complaint types.
- Provides configurable review depth and marketplace support.
- No extra dependencies or API keys needed; runs directly with Python 3.
Metadata
Frequently Asked Questions
What is Amazon Review Monitor?
Monitor Amazon product reviews by ASIN, analyze ratings and sentiment, identify issues, and draft AI-generated seller responses to negative feedback. It is an AI Agent Skill for Claude Code / OpenClaw, with 317 downloads so far.
How do I install Amazon Review Monitor?
Run "/install amazon-review-monitor" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Amazon Review Monitor free?
Yes, Amazon Review Monitor is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Amazon Review Monitor support?
Amazon Review Monitor is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Amazon Review Monitor?
It is built and maintained by Elway Botty (@avmw2025); the current version is v1.0.0.
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