Amazon Product Reviews

Fetch and analyze Amazon product reviews to help sellers extract actionable insights from customer feedback.

Core Concepts

This tool retrieves real customer reviews for a given Amazon ASIN across 15 marketplaces. You can control how many reviews to fetch per star rating (1-5 stars, up to 100 each), sort by recency or helpfulness, and apply various filters. Only one ASIN per request; for multiple ASINs, make separate calls.

API Invocation

• API Endpoint: POST /amazon/reviews/list (see references/api.md for full parameters/responses/error codes)
• Python Script: python scripts/amazon_reviews.py '<JSON params>' [--inline]
• Cost Constraints: This tool consumes credits. The same parameter combination in the same session is only called once by default, with 24h local caching in the script. Failed or empty results should not trigger automatic retries with different keywords, pagination, or postal codes. Inform the user before making additional queries that will incur extra costs.

Output Strategy (default script behavior):

• Always write the full response to <cwd>/nexscope/<YYYY-MM-DD>/<session>/data/nexscope-amazon-reviews-list-<timestamp>.json (<cwd> is the working directory at script execution time, which in Claude Code is the current project directory; <session> is taken from the SESSION_ID environment variable, auto-grouped by user task; do not write to /tmp, error out if the current directory is not writable)
• Response body less than or equal to 8 KB: print the full JSON to stdout after saving to disk
• Response body greater than 8 KB: after saving, stdout prints only a summary (top-level fields, common counts like total/costToken, length of the largest list field + first 3 samples)
• Add --inline to force full output to stdout (still saves to disk)

Data Reading Tips: Check the summary first to determine if it is sufficient. When specific fields are needed, use jq or ConvertFrom-Json to extract from the saved JSON file on demand, avoiding loading the entire JSON into context.

Authentication

Set the NEXSCOPE_API_KEY environment variable. If authentication fails (401/402) or you see insufficient balance errors, visit https://www.nexscope.ai/help/skills-external-access?co-from=skillNS to get an API Key or top up credits.

Parameter Guide

Parameter	Type	Required	Scope	Description	Default
asin	string	Yes	All	Amazon product ASIN	-
star1Num	integer	No	Main endpoint	1-star reviews to fetch (0-100)	10
star2Num	integer	No	Main endpoint	2-star reviews to fetch (0-100)	10
star3Num	integer	No	Main endpoint	3-star reviews to fetch (0-100)	10
star4Num	integer	No	Main endpoint	4-star reviews to fetch (0-100)	10
star5Num	integer	No	Main endpoint	5-star reviews to fetch (0-100)	10
sortBy	string	No	All	recent (newest) or helpful (most helpful)	recent
formatType	string	No	All	all_formats or current_format	all_formats
domainCode	string	No	Main endpoint	Marketplace code (see Supported Marketplaces); use com for US	com
filterByKeyword	string	No	Main endpoint	Filter reviews by keyword (max 1000 chars)	-
reviewerType	string	No	Main endpoint	all_reviews or avp_only_reviews (verified only)	all_reviews
mediaType	string	No	Main endpoint	all_contents or media_reviews_only	all_contents

Star Count Defaults

• If no star count fields are provided, star1Num to star5Num all default to 10.
• If any star count field is provided, unspecified star counts default to 0.

Supported Marketplaces

Marketplace	Code
United States	com
Canada	ca
United Kingdom	co.uk
Germany	de
France	fr
Italy	it
Spain	es
Japan	co.jp
India	in
Australia	com.au
Brazil	com.br
Mexico	com.mx
Netherlands	nl
Sweden	se
United Arab Emirates	ae

Use domainCode for every supported marketplace. Always confirm the user's intended marketplace.

Usage Examples

1. Fetch US reviews (Amazon.com)

{"asin": "B08N5WRWNW", "domainCode": "com", "star1Num": 10, "star2Num": 10, "star3Num": 10, "star4Num": 10, "star5Num": 10, "sortBy": "recent"}

2. Fetch negative reviews with keyword filter (Germany)

{"asin": "B08N5WRWNW", "domainCode": "de", "star1Num": 30, "star2Num": 30, "filterByKeyword": "quality", "reviewerType": "avp_only_reviews"}

3. Fetch 5-star reviews with media (Japan)

{"asin": "B08N5WRWNW", "domainCode": "co.jp", "star5Num": 50, "star1Num": 0, "star2Num": 0, "star3Num": 0, "star4Num": 0, "sortBy": "helpful", "mediaType": "media_reviews_only"}

4. Fetch only 3-star reviews (explicit star mode)

{"asin": "B0FP5C63HZ", "domainCode": "com", "star3Num": 100}

Display Rules

1. Present data clearly: Show reviews grouped by star rating with key fields: rating, title, text, date, verified status, helpful count.
2. Summarize when appropriate: For many reviews, provide a theme/pain-point summary before listing individuals.
3. Highlight actionable insights: Call out recurring complaints in negative reviews; note praised features in positive reviews.
4. Vine and verified labels: Clearly indicate Vine Voice and verified purchase status.
5. Media indicators: Note when reviews include images or videos.
6. Response normalization: Normalize rating and helpful-count fields for consistent display when the raw response uses marketplace-specific text formats.
7. Error handling: When a query fails, explain the reason based on the response message and suggest adjusting parameters.
8. Single ASIN limitation: If the user asks about multiple ASINs, make separate requests for each.

Important Limitations

• One ASIN per request: Only a single ASIN can be queried at a time.
• Per-star cap: Each star rating returns max 100 reviews per request.
• Parameter scope: filterByKeyword, reviewerType, mediaType are available on /amazon/reviews/list, including domainCode: "com".
• No historical snapshots: Reviews are fetched in real-time.
• Review text language: Reviews are returned in their original language as posted.

User Expression and Scenario Quick Reference

Applicable -- Tasks involving Amazon product reviews:

User Says	Scenario
"Show me the reviews for this ASIN"	Direct review lookup
"Get US reviews for B08N5WRWNW"	Marketplace-specific lookup
"What are customers complaining about"	Negative review analysis
"Get me all the 1-star reviews"	Star-filtered retrieval
"Any common issues in the bad reviews"	Pain point mining
"What do people like about this product"	Positive review analysis
"Find reviews mentioning battery"	Keyword-filtered reviews
"Show me reviews with photos"	Media-filtered reviews
"Verified purchase reviews only"	Reviewer-type filtering
"Help me analyze competitor reviews"	Competitor review research
"Product improvement suggestions from reviews"	Actionable insight extraction

Not applicable -- Needs beyond product review data:

• ABA search term data / keyword research (use ABA Data Explorer instead)
• Sales estimation or revenue analysis
• Listing copywriting or A+ content creation
• Advertising / PPC strategy
• Pricing strategy or profit margin calculations

Boundary judgment: If "product research" or "competitor analysis" boils down to reading customer reviews for specific ASINs, this skill applies. If it involves search volume, keyword rankings, sales estimates, or market sizing, it does not.