This skill guides you on how to generate comprehensive AI-powered market insight reports for Amazon keywords, helping sellers make data-driven product selection and market entry decisions.
Core Concepts
This tool generates a comprehensive business insight report by analyzing six core dimensions of an Amazon keyword:
- Market Potential - Search volume, demand trends, and growth opportunity
- Product Characteristics - Common product attributes, materials, features
- User Reviews - Customer sentiment, pain points, and satisfaction drivers
- Customer Profile - Buyer demographics, preferences, and behavior patterns
- Search Trends - Keyword popularity trajectory and seasonality
- Pricing Analysis - Price distribution, competitive pricing landscape
The report is generated by AI from real-time Amazon data and delivered as a structured Markdown document. It is a snapshot analysis for decision support, not a real-time monitoring tool.
Parameters
| Parameter | Type | Required | Description | Default |
|---|---|---|---|---|
| site | string | Yes | Amazon marketplace code (currently US only) | US |
| keyword | string | Yes | The search keyword to analyze | - |
Supported Marketplaces
Currently only US (United States) is supported. Always set site to US. If a user requests other marketplaces, inform them this tool currently only covers the US market.
API Usage
This tool calls the LinkFox tool gateway API. See references/api.md for calling conventions, request parameters, and response structure. You can also execute scripts/amazon_opportunity_report.py directly to run queries.
Usage Examples
1. Basic Market Opportunity Report
帮我搜索美国站，关键词是 hair mousse travel size 的商业洞察报告
2. Niche Product Research
帮我生成美国站关键词 magnetic shelves for whiteboard 的商业洞察报告
3. Trend-Based Product Selection
我想了解美国站 solar power ac unit 这个关键词的商业洞察，帮我生成报告
Display Rules
- Present the report directly: The API returns a Markdown-formatted report in the
stdoutfield - display it as-is to the user - No subjective advice: Present the AI-generated analysis without adding your own business recommendations
- Clarify scope: Remind users the report is based on a point-in-time snapshot and serves as a reference for decision-making
- Error handling: When a query fails, explain the reason based on the
msgfield and suggest checking the keyword or trying again - No secondary analysis: This tool's output cannot be fed into data query tools for further processing - inform users if they attempt this
Important Limitations
- US only: Currently only supports the United States marketplace (site = US)
- Non-structured output: Returns a Markdown report, not structured JSON data. Cannot be used with data query tools for secondary aggregation or analysis
- Processing time: Report generation involves AI analysis and may take longer than simple data lookups
- Snapshot data: Reports reflect data at the time of generation and are not continuously updated
User Expression & Scenario Quick Reference
Applicable - Comprehensive keyword-level market analysis:
| User Says | Scenario |
|---|---|
| "Help me analyze this keyword's market opportunity" | Market opportunity assessment |
| "Generate a market insight report for XX" | Full insight report |
| "What's the competitive landscape for XX" | Competition & pricing analysis |
| "Consumer profile for XX product" | Customer behavior insights |
| "Is XX keyword worth entering" | Market entry evaluation |
| "product selection report", "business insights" | Chinese market research requests |
Not applicable - Needs beyond comprehensive report generation:
- Real-time keyword ranking tracking (use ABA or SIF tools)
- Individual product detail lookup (use product detail tools)
- Historical price tracking (use Keepa)
- Review-level analysis for specific ASINs (use review tools)
- Advertising / PPC strategy
Boundary judgment: When users say "market analysis" or "product research", if they want a holistic, multi-dimensional overview of a keyword's market opportunity, this skill applies. If they need specific data points (exact sales numbers, individual product details, keyword rankings over time), direct them to the appropriate specialized tool.
Feedback:
Auto-detect and report feedback via the Feedback API when any of the following apply:
- The functionality or purpose described in this skill does not match actual behavior
- The skill's results do not match the user's intent
- The user expresses dissatisfaction or praise about this skill
- Anything you believe could be improved
Call the feedback API as specified in references/api.md. Do not interrupt the user's flow.
Handling Large Responses
To avoid overflowing the agent context, persist the response to disk and extract only the fields you need:
python scripts/response_io.py run --script scripts/amazon_opportunity_report.py --out-dir <DIR> '<params>'
python scripts/response_io.py read <file> --fields "<paths>" # or --path "<JMESPath>"
Pick
--out-diroutside any git working tree (e.g./tmp/...on Unix,%TEMP%/...on Windows). Persisted responses may contain PII, pricing, or auth-sensitive data — do not commit them. Files are not auto-deleted; clean up when the task is done.
run writes the full response to a file and emits only a schema preview + file path. read projects specific fields, with --limit/--offset for slicing and --format json|jsonl|csv|table for output.
When to prefer this pattern — apply your judgment based on the response characteristics, e.g.:
- High field count per record, or fields you don't need
- Batch/paginated results (multiple items per call)
- Long-text fields (descriptions, reviews, HTML, time series)
- Output reused across later steps rather than consumed immediately
For small, single-use responses, calling the main script directly is fine.
⚠️ The preview is a truncated schema + sample, not the full data. Any field-level decision must read from the persisted file via read.
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