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linkfox-keepa-product-series

Data & analytics

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Updated 10-15 11:35

About this skill

Keepa Product Time-Series Data Explorer

This skill guides you on how to query and analyze Amazon product historical time-series data, helping Amazon sellers track price movements, BSR trends, rating changes, and other key product metrics over time.

Core Concepts

This tool provides historical time-series data for individual Amazon products (ASINs) powered by Keepa. It returns timestamped data points for various metrics, allowing trend analysis over a configurable time window (up to 365 days). Each query targets a single ASIN in a specific Amazon marketplace.

Time-series format: All data series are returned as arrays of {time, value} objects, where time is a timestamp and value is the metric at that point. BSR data includes a categoryName field along with a points array. Analyze these fields from the saved JSON directly. _dataQuery_executeDynamicQuery reads Linkfox session data stored in SLS, not arbitrary JSON files; its supported data mappings do not determine whether these time series can be analyzed.

BSR logic: A smaller BSR value means a better sales rank. Rank 1 is the top-selling product in its category. When a user says "BSR improved", it means the numeric value decreased; "BSR dropped" means the value increased.

Available Data Series

Series Parameter Description
Buy Box Price (always returned) Buy Box price over time
Lowest New Price showPrice=1 Lowest marketplace new item price
List Price showPriceList=1 Strikethrough / list price
Deal Price showPriceDeal=1 Lightning deal price
Prime Exclusive Price showPricePrime=1 Prime-exclusive new item price
FBA Price showPriceFba=1 Third-party FBA new item price
FBM Price showPriceFbm=1 Third-party FBM new item price
Coupon Price showPriceCoupon=1 Post-coupon Buy Box price
Main Category BSR showBsrMain=1 Best Sellers Rank in the main (root) category
Seller Count showSellerCount=1 Number of active sellers
Rating (always returned) Product star rating over time
Rating Count (always returned) Number of ratings over time
Monthly Sales (always returned) Monthly unit sales volume
Sub-category BSR (always returned) Best Sellers Rank in sub-categories

Supported Marketplaces

Domain ID Marketplace
1 Amazon.com (US)
2 Amazon.co.uk (UK)
3 Amazon.de (Germany)
4 Amazon.fr (France)
5 Amazon.co.jp (Japan)
6 Amazon.ca (Canada)
8 Amazon.it (Italy)
9 Amazon.es (Spain)
10 Amazon.in (India)
11 Amazon.com.mx (Mexico)
12 Amazon.com.br (Brazil)

Default marketplace is 1 (US). Use domain=1 when the user does not specify a marketplace.

How to call

  • API endpoint:POST /keepa/productSeries(for full parameters/responses/error codes, see references/api.md)
  • Python script:python scripts/keepa_product_history.py '<JSON 参数>' [--inline]
  • Cost constraints: This tool consumes compute; by default, the same parameter combination in the same session is called only once, and the script has a 24h local cache. On failure/empty results, do not automatically try successive probes by changing keywords, paging, or changing the zip code; if further retrieval is needed, first explain to the user that it will incur additional consumption.

Output strategy (script default behavior):

  • Alwayswrite the full response to <cwd>/linkfox/<YYYY-MM-DD>/<session>/data/linkfox-keepa-product-series-<timestamp>.json(<cwd> is the working directory when the script runs, which in Claude Code is the current project directory;<session> is taken from the environment variable SESSION_ID, automatically aggregated according to the user's task;writing to /tmp is prohibited, and if the current directory is not writable, report an error)
  • Response body ≤ 8 KB: after saving to disk, print the full JSON to stdout
  • Response body > 8 KB: after saving to disk, stdout outputs only a summary (top-level fields, common counts such as total/costToken, the length of the largest list field + the first 3 samples)
  • Add --inline to force full printing to stdout (also saved to disk)

Data reading suggestions: First look at the summary to determine whether it is sufficient; when specific fields are needed, prefer using jqorConvertFrom-Json to extract on demand from the saved json file, avoiding bringing the entire JSON into context.

Resolve authentication and compute issues

When the following abnormal situations occur, use references/onboarding.md to guide resolution:

Abnormal situations

  • API Key not configured: The environment variable is not configured LINKFOX_AGENT_API_KEY, and LINKFOXAGENT_API_KEY。
  • Response 401 or 402 status code
  • Response indicates insufficient compute or balance: The message contains "insufficient compute balance/insufficient billing/insufficient balance/quota exceeded/insufficient balance/package expired/recharge required/please recharge", or content with a similar meaning.

Parameter Guide

Required Parameters

  • asin: The Amazon Standard Identification Number to query. Only a single ASIN per request is supported.
  • domain: The Amazon marketplace domain ID (see table above). Always map the user's marketplace mention to the correct numeric ID.

Optional Parameters

  • days: Number of historical days to retrieve (1-365, default 90). Use 30 for short-term, 90 for medium-term, 365 for long-term analysis.
  • show* flags: Set any show* parameter to 1 to include that data series. By default, only the core series (Buy Box price, rating, rating count, monthly sales, sub-category BSR) are returned.

How to Choose Parameters

  1. Price analysis: Enable showPrice, showPriceList, showPriceDeal, showPriceCoupon as needed for the specific price comparison the user wants.
  2. FBA vs FBM comparison: Enable both showPriceFba and showPriceFbm.
  3. BSR deep-dive: Enable showBsrMain to get the root category BSR alongside the always-returned sub-category BSR.
  4. Competitive landscape: Enable showSellerCount to see how many sellers are competing.
  5. Full product overview: Enable all show flags for a comprehensive historical snapshot.

Usage Examples

1. Basic price history for a US product

asin: B0XXXXXXXX, domain: 1, days: 90

2. Long-term BSR trend (1 year) on the German marketplace

asin: B0XXXXXXXX, domain: 3, days: 365, showBsrMain: 1

3. Price comparison across fulfillment channels

asin: B0XXXXXXXX, domain: 1, days: 30, showPriceFba: 1, showPriceFbm: 1, showPrice: 1

4. Deal and coupon price tracking

asin: B0XXXXXXXX, domain: 1, days: 90, showPriceDeal: 1, showPriceCoupon: 1

5. Full product health check

asin: B0XXXXXXXX, domain: 1, days: 90, showPrice: 1, showPriceList: 1, showPriceDeal: 1, showPricePrime: 1, showPriceFba: 1, showPriceFbm: 1, showPriceCoupon: 1, showBsrMain: 1, showSellerCount: 1

Display Rules

  1. Present data clearly: Show time-series data in tables or describe trends; avoid subjective business advice unless the user explicitly asks for it.
  2. BSR clarification: When showing BSR data, remind users that lower values mean better (higher) sales ranks.
  3. Price formatting: Display prices with proper currency symbols matching the marketplace ($ for US, EUR for DE/FR/ES/IT, GBP for UK, JPY for JP, etc.).
  4. Time formatting: Present timestamps in a human-readable date format.
  5. Trend summarization: When data series are long, summarize the overall trend (e.g., "price decreased from $29.99 to $24.99 over 90 days") and highlight significant changes such as price drops, BSR spikes, or rating shifts.
  6. Error handling: When a query fails, explain the reason and suggest corrections (e.g., verify the ASIN is valid, check the marketplace domain ID).
  7. Single ASIN limitation: If the user asks about multiple ASINs, inform them that queries must be made one ASIN at a time, and run multiple sequential calls.

Important Limitations

  • Single ASIN per query: Only one ASIN can be queried at a time. For multi-ASIN comparisons, make separate requests.
  • Maximum 365 days: Historical data is limited to at most 365 days back.
  • Data granularity: Data points are at irregular intervals depending on when Keepa captured changes, not at fixed daily intervals.

User Expression & Scenario Quick Reference

Applicable -- Historical product-level data queries on Amazon:

User Says Scenario
"What's the price history for this ASIN" Price trend analysis
"Show me the BSR trend", "how is it ranking" BSR tracking
"Has the price dropped recently", "any deals" Price drop / deal detection
"How many sellers are on this listing" Seller count trend
"What's the rating trend", "review count over time" Rating / review tracking
"FBA vs FBM price", "who has the Buy Box" Fulfillment price comparison
"Monthly sales for this product" Sales volume trend
"Was there a price war on this ASIN" Competitive pricing analysis
"Show me the Keepa chart", "Keepa data" Explicit Keepa data requests

Not applicable -- Needs beyond product-level historical data:

  • Search term / keyword analysis (use ABA data instead)
  • Advertising / PPC campaign data
  • Listing copywriting or content optimization
  • Category-wide or market-level aggregate trends (this tool is per-ASIN only)
  • Real-time inventory or stock level checks
  • Product reviews text or sentiment analysis

Boundary judgment: When users say "product research" or "competitor analysis", if it boils down to examining a specific ASIN's historical price, BSR, or sales data, this skill applies. If they need keyword data, market-wide trends, or advertising metrics, it does not apply.

Compute consumption rules

Billed according to dynamic rules: compute consumed = 0.045 × the Keepa tokens consumed by this historical trend query.

Important: The service of this skill is dynamically calculated by a multiplier and may consume a large amount of compute at once. The user must be reminded, and the user decides whether to continue.

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.


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