linkfox-keepa-product-series

name	linkfox-keepa-product-series
description	查询亚马逊商品的历史时序数据，包括价格走势、BSR（畅销排名）趋势、评分变化、卖家数量和月销量，支持多个亚马逊站点的任意ASIN。当用户提到价格历史、价格追踪、BSR历史、BSR趋势、历史定价、价格波动、Keepa数据、排名历史、降价提醒、秒杀历史价格、Buy Box价格趋势、优惠券价格、FBA/FBM价格对比、卖家数量变化、评分趋势、销量历史、price history, BSR trends, Keepa historical data, price tracking, sales history, rating changes, seller count changes, price fluctuation时触发此技能。即使用户未明确提及"Keepa"或"时序数据"，只要其需求涉及亚马逊历史商品级数据（如价格、排名或销量随时间的变化趋势），也应触发此技能。

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.

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.

调用方式

• API 端点：POST /keepa/productSeries（完整参数/响应/错误码见 references/api.md）
• Python 脚本：python scripts/keepa_product_history.py '<JSON 参数>' [--inline]
• 成本约束：本工具会消耗积分；同一会话同一参数组合默认只调用一次，脚本带 24h 本地缓存。失败/空结果不得自动换关键词、翻页或改邮编连续试探；需要继续检索时先向用户说明会产生额外消耗。

输出策略（脚本默认行为）：

• 始终将完整响应写入 <cwd>/linkfox/<YYYY-MM-DD>/<session>/data/linkfox-keepa-product-series-<timestamp>.json（<cwd> 为脚本执行时的工作目录，在 Claude Code 里即当前项目目录；<session> 取自环境变量 SESSION_ID，按用户任务自动聚合；禁止写入 /tmp，当前目录不可写则报错）
• 响应体 ≤ 8 KB：落盘后把完整 JSON 打印到 stdout
• 响应体 > 8 KB：落盘后 stdout 只输出摘要（顶层字段、常见计数如 total/costToken、最大列表字段的长度 + 前 3 条样本）
• 加 --inline 强制全量打印到 stdout（同样落盘）

读数据建议：先看摘要判断是否足够；需要具体字段时优先用 jq或ConvertFrom-Json 从保存的 json 文件按需抽取，避免整份 JSON 进入上下文。

解决认证和积分问题

发生以下异常情况时，采用 references/onboarding.md 引导解决问题：

异常情况

• 未配置API Key：环境变量未配置 LINKFOX_AGENT_API_KEY，也未配置 LINKFOXAGENT_API_KEY。
• 响应401或402状态码
• 响应提示积分或余额不足：消息含"积分余额不足/计费不足/余额不足/quota exceeded/insufficient balance/套餐到期/需充值/请充值"，或类似含义的内容。

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.

积分消耗规则

按动态规则计费：消耗积分 = 0.045 × 本次历史趋势查询消耗的 Keepa token。

重要：本技能的服务按倍数动态计算，可能一次性消耗大量积分，必须提醒用户，由用户决定是否继续。

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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