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Linkfox Jiimore Product Discovery

  • 233 installs
  • 64 repo stars
  • Updated August 3, 2026
  • linkfox-ai/linkfox-skills

Helps with ai & agent building tasks.

About

linkfox-jiimore-product-discovery is a Claude Code skill in the AI & Agent Building category.

  • linkfox-jiimore-product-discovery
  • AI & Agent Building
  • AI-coding skill

Linkfox Jiimore Product Discovery by the numbers

  • 233 all-time installs (skills.sh)
  • +35 installs in the week ending Aug 2, 2026 (Skillselion tracking)
  • Ranked #2,640 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Aug 4, 2026 (Skillselion catalog sync)
npx skills add https://github.com/linkfox-ai/linkfox-skills --skill linkfox-jiimore-product-discovery

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Listed on Skillselion
Installs233
repo stars64
Last updatedAugust 3, 2026
Repositorylinkfox-ai/linkfox-skills

What it does

Helps with ai & agent building tasks.

Files

SKILL.mdMarkdownGitHub ↗

Jiimore Product Discovery

This skill guides you on how to discover and mine high-potential Amazon products using the Jiimore product discovery engine, helping Amazon sellers find potential bestsellers through keyword-based filtering with conversion, click growth, and profitability indicators.

Core Concepts

Jiimore Product Discovery is a keyword-driven Amazon product mining tool. Given a search keyword, it returns a list of products matching specified performance criteria such as conversion rate, click growth rate, gross profit margin, pricing, reviews, and listing age. This makes it ideal for identifying emerging opportunities, validating product ideas, and competitive benchmarking.

Keyword is required: Every query must include a keyword. The keyword should be translated into the language of the target marketplace (e.g., Japanese for JP, German for DE).

Rate values are decimals: Conversion rates and growth rates are expressed as decimals between 0 and 1. For example, 0.1 means 10%, 0.25 means 25%. This is a common point of confusion when users specify percentages.

Marketplace support: Currently supports US (United States), JP (Japan), and DE (Germany). Default is US. Use US when the user doesn't specify a marketplace.

Parameter Guide

Required

ParameterDescriptionExample
keywordSearch keyword (must be translated to the target marketplace language)wireless charger

Filtering Parameters

ParameterDescriptionValue Format
priceMin / priceMaxProduct price rangeNumber (e.g., 10.0, 50.0)
totalReviewsMin / totalReviewsMaxReview count rangeInteger (e.g., 0, 500)
customerRatingMin / customerRatingMaxCustomer rating rangeNumber (e.g., 4.0, 5.0)
clickConversionRateMin / clickConversionRateMaxClick-to-purchase conversion rateDecimal 0-1 (0.1 = 10%)
clickConversionRateCompositeMin / clickConversionRateCompositeMaxComposite conversion rateDecimal 0-1 (0.1 = 10%)
clickCountT7Min / clickCountT7MaxWeekly click count rangeInteger
clickCountT30Min / clickCountT30MaxMonthly click count rangeInteger
clickCountGrowthT7Min / clickCountGrowthT7MaxWeekly click growth rateDecimal 0-1 (0.1 = 10%)
clickCountGrowthT30Min / clickCountGrowthT30MaxMonthly click growth rateDecimal 0-1 (0.1 = 10%)
salesVolumeT360Min / salesVolumeT360MaxAnnual sales volume rangeInteger
grossProfitMarginMin / grossProfitMarginMaxGross profit margin rangeNumber
fbaFeeMin / fbaFeeMaxFBA fee rangeNumber
launchDateMin / launchDateMaxListing date rangeString: yyyyMMdd000000
nicheCountMin / nicheCountMaxNiche market count rangeInteger
sellerCountrySeller origin country code(s), comma-separatedCN,US
countryCodeTarget marketplace (US, JP, DE)US

Sorting & Pagination

ParameterDescriptionDefault
sortFieldSort by field (see options below)purchasedClicksT360
sortTypeSort direction: desc or ascdesc
pagePage number1
pageSizeResults per page (10-100)50

Available sort fields: totalReviews, price, launchDate, clickCountT7, clickCountT30, clickCountT90, clickConversionRate, clickConversionRateComposite, customerRating, purchasedClicksT360, clickCountGrowthT7, clickCountGrowthT30, currentPrice, fbaFee, shippingFee, gpm

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/jiimore_product_discovery.py directly to run queries.

Usage Examples

1. Find high-conversion wireless chargers in the US market

{
  "keyword": "wireless charger",
  "countryCode": "US",
  "clickConversionRateMin": 0.1,
  "sortField": "clickConversionRate",
  "sortType": "desc"
}

2. Discover fast-growing new products (listed within the last 6 months, weekly click growth > 20%)

{
  "keyword": "desk lamp",
  "countryCode": "US",
  "launchDateMin": "20250901000000",
  "clickCountGrowthT7Min": 0.2,
  "sortField": "clickCountGrowthT7",
  "sortType": "desc"
}

3. Find underpriced high-margin products with low competition (few reviews)

{
  "keyword": "phone stand",
  "countryCode": "US",
  "priceMin": 10,
  "priceMax": 30,
  "totalReviewsMax": 100,
  "grossProfitMarginMin": 0.3,
  "sortField": "gpm",
  "sortType": "desc"
}

4. Mine products from Chinese sellers with strong monthly click growth in the German market

{
  "keyword": "Handyhuelle",
  "countryCode": "DE",
  "sellerCountry": "CN",
  "clickCountGrowthT30Min": 0.15,
  "sortField": "clickCountGrowthT30",
  "sortType": "desc"
}

5. Find high-rated products with strong annual sales in the Japanese market

{
  "keyword": "ワイヤレスイヤホン",
  "countryCode": "JP",
  "customerRatingMin": 4.0,
  "salesVolumeT360Min": 1000,
  "sortField": "purchasedClicksT360",
  "sortType": "desc"
}

6. Identify niche opportunities with high composite conversion and multiple niche markets

{
  "keyword": "yoga mat",
  "countryCode": "US",
  "clickConversionRateCompositeMin": 0.15,
  "nicheCountMin": 3,
  "sortField": "clickConversionRateComposite",
  "sortType": "desc"
}

Display Rules

1. Present data clearly: Show query results in well-structured tables, including product title, ASIN, price, ratings, conversion rates, click counts, and growth rates 2. Rate formatting: Always display rate values as percentages for readability (e.g., show 0.12 as 12%). Remind users that the API accepts decimals (0-1) 3. Image display: When product image URLs are available, display the main product image alongside the data 4. Pagination awareness: When results span multiple pages, inform the user of the total count and current page, and offer to fetch additional pages 5. Keyword translation reminder: Remind users that keywords must be in the target marketplace language (English for US, Japanese for JP, German for DE) 6. Error handling: When a query fails, explain the reason based on the response and suggest adjusting query criteria 7. No subjective advice: Present factual product data without making subjective business recommendations

Important Limitations

  • Keyword is mandatory: Every query requires a keyword; browsing without a keyword is not supported
  • Three marketplaces only: Currently limited to US, JP, and DE
  • Page size cap: Maximum 100 results per page
  • Rate values: All rate/percentage parameters must be passed as decimals (0-1), not percentages
  • Launch date format: Must follow the yyyyMMdd000000 format exactly (e.g., 20250101000000)

User Expression & Scenario Quick Reference

Applicable -- Product discovery and mining tasks:

User SaysScenario
"Find hot products for keyword X"Keyword-based product discovery
"High conversion products", "best sellers"High-conversion product screening
"Fast growing products", "trending items"Click growth-based discovery
"New products with high potential"New listing + growth filtering
"Products with good margins", "profitable items"Gross profit margin screening
"Low competition products", "few reviews"Low-review opportunity mining
"Products from Chinese sellers"Seller origin filtering
"Niche market opportunities"Niche count-based discovery

Not applicable -- Needs beyond product discovery:

  • ABA search term data and keyword analysis (use ABA Data Explorer)
  • Advertising / PPC campaign management
  • Product reviews and listing optimization
  • Inventory management and supply chain
  • Comprehensive market reports with profit/pricing strategy

Feedback:

Auto-detect and report feedback via the Feedback API when any of the following apply: 1. The functionality or purpose described in this skill does not match actual behavior 2. The skill's results do not match the user's intent 3. The user expresses dissatisfaction or praise about this skill 4. Anything you believe could be improved

Call the feedback API as specified in references/api.md. Do not interrupt the user's flow.

<!-- LF_LARGE_RESPONSE_BLOCK -->

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/jiimore_product_discovery.py --out-dir <DIR> '<params>'
python scripts/response_io.py read <file> --fields "<paths>"   # or --path "<JMESPath>"
Pick --out-dir outside 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. <!-- /LF_LARGE_RESPONSE_BLOCK -->

--- For more high-quality, professional cross-border e-commerce skills, set [LinkFox Skills](https://skill.linkfox.com/).

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