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pangolinfo

PangolinFo Amazon Ad Tracker & Review Intelligence

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by pangolinfo

list_seller_products

List all products from an Amazon seller by merchant ID. Paginated results include ASIN, title, price, and ratings for competitive analysis.

Instructions

[Amazon 卖家店铺铺货] 列出某 merchant ID 名下的全部上架商品,分页(每页 24 条)。 Use when: 用户说"看一下这个卖家有哪些产品""X 店铺铺了多少 SKU""竞品店铺品类宽度""跟卖卖家在卖什么""店铺铺货策略调研"。 Don't use: 不知道 merchant ID 时(先去某商品 PDP 里找 'sold by' 链接拿 ID);只看单品(用 get_amazon_product)。 Returns: data.json[0].data.{ pageIndex, maxPage, nextPage, results[{ asin, title, price, star, rating, rank, img }] } —— 每页 24 条。翻页: 用 page 参数(默认 1,从 1 开始);nextPage 为下一页页码,nextPage=null 或 page>=maxPage 表示到底。 Pair with: ↑ sellerId 通常从 get_amazon_product 的 seller.id 字段拿到,或用户从 amazon.com/sp?seller=... URL 里读到;↓ 把 asin 喂 get_amazon_product 拆主推品。 Cost: ~1 积点/页, ~5s。 Tips: 跟卖矩阵分析需要全 SKU 时才翻 2-3 页;单纯看一下店铺有什么货首页就够。Amazon 自营 sellerId = 'ATVPDKIKX0DER'。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sellerIdYesAmazon 卖家 ID(merchant ID,14 位字母数字)。Examples: 'ATVPDKIKX0DER'(Amazon 自营)/ 'A2L77EE7U53NWQ'(Amazon Warehouse)。从商品页 'sold by' 链接或 amazon.com/sp?seller=... URL 里读取。
siteNoAmazon 站点。默认 amz_us。amz_us
zipcodeNo邮编,必须匹配 site 站点所在国家(amz_us → 美国邮编,amz_jp → 日本邮编 …)。可选;不传时后端会从对应国家邮编池随机挑一个。跨国邮编(如 amz_us + 日本邮编)会被后端拒绝。Examples: 10001 (NY) / 90001 (LA) / 100-0001 (Tokyo).
formatNo返回格式。默认 'json'——结构化卖家商品列表。需要原始页面阅读时切 'markdown'。json
pageNo页码,从 1 开始。每页 24 条。结合响应里的 pageIndex/maxPage/nextPage 决定是否继续:nextPage 为下一页页码,nextPage=null 或 page>=maxPage 表示到底。**只在用户明确要更多/全部 SKU 时才翻**,否则首页够用。
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description fully discloses pagination (24 per page, page indices, nextPage logic), response structure, cost (~1 point, ~5s), and tips (e.g., Amazon self sellerId, when to paginate). It lacks an explicit 'read-only' statement but implies non-destructive behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is structured with clear sections (purpose, use/don't use, returns, pair with, cost, tips). It is front-loaded with the main function. While lengthy, every sentence adds value; could be slightly trimmed but remains efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 5 parameters, no output schema, and 18 sibling tools, the description covers purpose, usage, parameter details, pagination logic, cost, and tips. It lacks explicit error handling or field descriptions in results, but the response structure is outlined. Overall sufficient for agent use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description adds significant context: examples and source for sellerId, zipcode cross-country rules, enums for site and format, and pagination details for page parameter. It also explains output structure to link parameters to results.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool lists all listed products for a merchant ID with pagination (24 per page). It distinguishes from siblings like get_amazon_product (single product) and list_category_products (category-level listing) by specifying 'seller' scope and mentioning paired usage.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit 'Use when' and 'Don't use' sections with example user queries and mistaken cases. It advises against using without merchant ID (directs to product page) and for single product (use get_amazon_product). Also pairs with get_amazon_product for seller ID extraction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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