Product Opportunity Finder v2.2.0IMPORTANT — 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
cdinto 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.
Product Understanding Step
Before running this skill, if the user provides a product, image, ASIN, listing, product ID, or product idea, first identify:
- product type/category
- main use case
- key physical, design, or functional features
- target marketplace, country, or platform
- user's analysis goal
Use this product understanding to choose parameters, filters, competitors, regions, keywords, or analysis dimensions before executing the script.
What products should I sell?
Find blue ocean products with multi-dimensional filtering and opportunity scoring.
Core Question
— What products should I sell? — What product opportunities are there?
When to Use
- Looking for product ideas to sell
- Filtering through a large category for opportunities
- Finding gaps in the market
- Discovering underserved niches
Differs From / Not Applicable
- Use product-validator when the user already has a specific ASIN/product.
- Use market-overview for broad market context.
- Use niche-evaluator for entry scoring.
- Use this skill for discovering product ideas and blue-ocean opportunities.
Data Sources
| Source | Endpoint | Data |
|---|---|---|
| Amazon Search | /api/v1/tools/research/amazon/search |
Products, sales, reviews |
| eBay | /api/v1/tools/research/ebay/search |
Cross-platform demand validation |
| Walmart | /api/v1/tools/research/walmart/search |
Multi-channel opportunity |
| Google Trends | /api/v1/tools/research/googleTrend/getTrendByKeys |
Trend validation |
| Keepa | /api/v1/tools/research/keepa/productRequest |
Product details, monthly sales |
| Keepa | /api/v1/tools/research/keepa/productSeries |
BSR/price history |
Opportunity Score (0-100)
Multi-dimensional score based on:
| Dimension | Weight | Metrics |
|---|---|---|
| 📈 Demand | 25% | Sales velocity, search volume |
| ⚔️ Competition | 25% | Review barriers, brand presence |
| 💰 Profit | 25% | Margins, price stability |
| 🎯 Opportunity | 25% | Gaps, differentiation |
Opportunity Types
| Type | Description |
|---|---|
| 🏖️ Low Competition | High demand, few sellers |
| ⭐ Quality Gap | Low ratings, room for improvement |
| 💵 Price Gap | Underserved price segment |
| 📈 Rising Star | Growing demand trend |
| 🔄 Channel Arbitrage | Price difference across platforms |
| 📦 Bundle Opportunity | FBT (frequently bought together) |
| 🎯 Niche Segment | Underserved sub-category |
Filter Presets
| Preset | Description |
|---|---|
| Conservative | Low risk, proven demand |
| Balanced | Mix of risk/reward |
| Aggressive | Higher risk, higher potential |
| Premium | High-price products |
| Budget | Low-price, high-volume |
| Trending | Focus on rising trends |
Red Lines (Auto-Exclude)
| Category | Reason |
|---|---|
| ⚠️ Hazmat | Shipping restrictions |
| ⚠️ Fragile | High damage rates |
| ⚠️ Patent/IP Risk | Legal issues |
| ⚠️ Oversized | FBA fee impact |
| ⚠️ Gated Category | Approval required |
⚠️ MANDATORY: Charts & Display Rules
- Generate charts by default for full analytical reports — use
--chartwith an output directory unless the user asks for a quick text-only result or chart data is unavailable. - Send generated charts to the user — when charts are created, share all chart PNGs immediately.
- All chart styling is driven by
ecommerce_chart_helpers.pywhich reads fromchart_style.json(derived fromreferences/display-rules.md). Do NOT hardcode colors in scripts.
Usage
# Find opportunities in a category
python3 scripts/product_opportunity_finder.py '{"keyword": "yoga accessories"}'
# With specific preset
python3 scripts/product_opportunity_finder.py '{"keyword": "kitchen gadgets", "preset": "conservative"}'
# Custom filters
python3 scripts/product_opportunity_finder.py '{"keyword": "pet supplies", "min_price": 10, "max_reviews": 500}'
# Multi-platform analysis
python3 scripts/product_opportunity_finder.py '{"keyword": "phone cases", "platforms": ["amazon"]}'
# With chart output
python3 scripts/product_opportunity_finder.py '{"keyword": "yoga mat"}' --chart /tmp/output
Parameters
| Parameter | Type | Default | Description |
|---|---|---|---|
keyword |
string | required | Category keyword |
market |
string | Target marketplace | |
preset |
string | "balanced" | Filter preset |
min_price |
float | - | Minimum price |
max_price |
float | - | Maximum price |
min_sales |
int | - | Minimum monthly sales |
max_reviews |
int | - | Maximum review count |
platforms |
array | ["amazon"] | Platforms to analyze |
Output Structure
The output will be a structured markdown report, following this format:
Product Opportunity Analysis Report: [Keyword, e.g., "Skincare"]
1. Executive Summary
- Analysis Date: [analysis_date]
- Total Products Analyzed: [products_searched count]
- Total Opportunities Found: [opportunities_found count]
- Overall Market Health: [insights.market_health, e.g., Good, Highly Competitive]
- Key Insight: [insights.summary]
2. Market Overview
- Average Product Price: [market_stats.avg_price]
- Average Review Count: [market_stats.avg_reviews]
- Average Rating: [market_stats.avg_rating]
- Price Distribution:
- Budget Products: [market_stats.price_distribution.budget]%
- Mid-Range Products: [market_stats.price_distribution.mid]%
- Premium Products: [market_stats.price_distribution.premium]%
- Cross-Platform Demand Validation:
- eBay: [cross_platform.ebay.sold_count] sales, Demand Level: [cross_platform.ebay.demand_level]
- Walmart: Found [cross_platform.walmart.product_count] products
- Trend Validation (Google Trends):
- Trend Direction: [trend_validation.google_trends.direction]
- Change Percentage: [trend_validation.google_trends.change_pct]%
3. Top Product Opportunities
- Recommended products ranked by Opportunity Score:
| Rank | ASIN | Product Name | Brand | Price | Monthly Sales | Score | Grade | Opportunity Type |
|---|---|---|---|---|---|---|---|---|
| 1 | [opportunities[0].asin] | [opportunities[0].title] | [opportunities[0].brand] | [opportunities[0].price] | [opportunities[0].monthly_sales] | [opportunities[0].score] | [opportunities[0].grade] | [opportunities[0].opportunity_types] |
| 2 | ... | ... | ... | ... | ... | ... | ... | ... |
(Showing top 5-10 opportunities)
4. Opportunity Type Distribution
- Statistics for different opportunity types:
| Opportunity Type | Count |
|---|---|
| Low Competition (LOW_COMPETITION) | [insights.opportunity_types.LOW_COMPETITION] |
| Quality Gap (QUALITY_GAP) | [insights.opportunity_types.QUALITY_GAP] |
| Price Gap (PRICE_GAP) | [insights.opportunity_types.PRICE_GAP] |
| Rising Star (RISING_STAR) | [insights.opportunity_types.RISING_STAR] |
| Channel Arbitrage (CHANNEL_ARBITRAGE) | [insights.opportunity_types.CHANNEL_ARBITRAGE] |
| Niche Segment (NICHE_SEGMENT) | [insights.opportunity_types.NICHE_SEGMENT] |
| (Other types, if any) |
5. Actionable Recommendations
- [insights.recommendations[0]]
- [insights.recommendations[1]]
- [insights.recommendations[2]]
- (Listing all key recommendations)
6. Attached Visualizations
- Seasonal Trend (seasonality.png)
- Segment Opportunities (segments.png)
- ROI Waterfall (roi_waterfall.png)
- Radar Score (radar.png)
- Product Comparison (comparison.png)
Charts Generated
| Chart | Description | File |
|---|---|---|
| Seasonality Trend | Monthly pattern | seasonality.png |
| Segment Opportunities | By type bar | segments.png |
| ROI Waterfall | Margin breakdown | roi_waterfall.png |
| Radar Score | Multi-dimension | radar.png |
| Product Comparison | Top opportunities | comparison.png |
Bundling Detection
| Signal | Description |
|---|---|
| FBT Match | Products frequently bought together |
| Complementary | Same customer, different need |
| Accessory | Main product + add-ons |
Workflow Integration
🎯 Selection Phase
├── product-opportunity-finder → Find specific products ← YOU ARE HERE
└── new-product-tracker → Track rising products
Environment Variables
| Variable | Required | Description |
|---|---|---|
NEXSCOPE_API_KEY |
Yes | NexScope proxy API key |
NEXSCOPE_PROXY_BASE |
Yes | NexScope proxy base URL |
Limitations
- Sales estimates are approximations
- Red line detection is keyword-based
- Bundling requires FBT data availability
- Cross-platform arbitrage changes rapidly
- Category cleaner may filter opportunities
References
references/opportunity-types.md— Opportunity definitionsreferences/visualization.md— Chart specificationsreferences/display-rules.md— Chart styling guidelines
Multi-Batch Usage
When analyzing more items than you want to run in a single invocation, keep charts and reports aligned by saving each batch as raw JSON and then generating one merged result.
Step 1: run each batch with --output to save intermediate JSON.
python3 scripts/product_opportunity_finder.py '{"keyword": "example"}' --output /tmp/batch1.json
python3 scripts/product_opportunity_finder.py '{"keyword": "example 2"}' --output /tmp/batch2.json
Step 2: merge every batch JSON and generate the final unified chart.
python3 scripts/product_opportunity_finder.py --merge /tmp/batch1.json /tmp/batch2.json --sort score --chart /tmp/final-charts
Use the merged JSON output and /tmp/final-charts/merged_ranking.png for the final report. Do not present per-batch charts as final charts when the text report has been globally re-ranked.