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apiclaw-amazon-apiapiclaw amazon API 搜索

Agent Skill

用于辅助 API 设计、接口文档、请求响应结构和服务集成说明。它适合让 Agent 梳理 endpoint、生成 OpenAPI 草稿、检查字段命名、整理错误码或辅助前后端联调。使用时需要确认真实业务语义、鉴权方式、分页和错误处理规则;涉及生成接口文档时,应避免凭空补字段,最好从现有代码、schema 或接口样例中提取事实。

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:apiclaw-amazon-api(apiclaw amazon API 搜索)
来源仓库:https://github.com/christine-srp/apiclaw-amazon-api
安装命令:
openclaw skills install apiclaw-amazon-api
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

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openclaw skills install apiclaw-amazon-api

简介

提供对超 2 亿亚马逊产品的编程级数据访问能力。

  • 适用于电商选品、竞品监控与市场分析场景。apiclaw-amazon-api 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 覆盖六大电子平台的实时商业数据基础设施。
  • 安装命令:openclaw skills install apiclaw-amazon-api。
  • 需遵守 Amazon 数据使用政策及相关法律条款。

SKILL.md

name
apiclaw
description
APIClaw API platform overview — AI-powered commerce data infrastructure. Provides programmatic access to 200M+ Amazon products with real-time data across 6 endpoints: category browsing, market metrics, product search, competitor lookup, realtime ASIN detail, and AI review analysis. Use when user asks: what APIClaw can do, available API endpoints, how to get started, API capabilities overview, credit usage, or general commerce data questions. For deep Amazon product selection strategies and analysis workflows, use the Amazon-analysis-skill instead. Requires APICLAW_API_KEY.
metadata
{"openclaw": {"requires": {"env": ["APICLAW_API_KEY"]}, "primaryEnv": "APICLAW_API_KEY"}}

APIClaw — Commerce Data Infrastructure for AI Agents

Real-time access to 200M+ Amazon products. 6 endpoints, one API key. Language rule: Respond in the user's language.

Quick Start

  1. Get API key: apiclaw.io/api-keys
  2. Set env: export APICLAW_API_KEY='hms_live_xxx'
  3. Base URL: https://api.apiclaw.io/openapi/v2
  4. Auth: Authorization: Bearer YOUR_API_KEY
  5. All endpoints: POST with JSON body

New keys need 3-5 seconds to activate. If 403, wait and retry.

API Endpoints

#EndpointWhat It DoesKey Output
1categoriesBrowse Amazon category treecategoryName, categoryPath, productCount, hasChildren
2markets/searchMarket-level aggregate metricssampleAvgMonthlySales, sampleAvgPrice, sampleBrandCount, topSalesRate, sampleFbaRate
3products/searchProduct search with 14 preset strategiesasin, title, price, bsrRank, atLeastMonthlySales, rating, ratingCount
4products/competitor-lookupCompetitor analysis by keyword/ASINcompetitive products with sales, revenue, seller info
5realtime/productLive single-ASIN detailtitle, rating, features, variants, bestsellersRank, buyboxWinner
6reviews/analyzeAI-powered review insightssentimentDistribution, consumerInsights (painPoints, buyingFactors, etc.)

Endpoint Details

1. Categories

Browse or search Amazon's category hierarchy.

POST /openapi/v2/categories
{"categoryKeyword": "pet supplies"}                    # search by keyword
{"parentCategoryPath": ["Pet Supplies"]}               # browse children

⚠️ Use categoryKeyword (not keyword) and parentCategoryPath (not parentCategoryName).

2. Markets

Category-level market metrics — answer "Is this market worth entering?"

POST /openapi/v2/markets/search
{"categoryPath": ["Pet Supplies", "Dogs", "Toys"], "topN": "10"}

⚠️ topN must be a string ("3", "5", "10", "20"), NOT an integer.

Returns: sampleAvgMonthlySales, sampleAvgPrice, sampleBrandCount, sampleSellerCount, topSalesRate (concentration), sampleNewSkuRate, sampleFbaRate.

3. Products

Product search with filters or 14 built-in selection modes.

POST /openapi/v2/products/search
{"keyword": "yoga mat", "mode": "beginner"}

14 modes: beginner, fast-movers, emerging, long-tail, underserved, new-release, fbm-friendly, low-price, single-variant, high-demand-low-barrier, broad-catalog, selective-catalog, speculative, top-bsr.

Key fields: atLeastMonthlySales (lower-bound estimate), bsrRank (integer), ratingCount (not reviewCount), price, profitMargin, fbaFee.

4. Competitors

Competitor discovery by keyword, brand, or specific ASIN.

POST /openapi/v2/products/competitor-lookup
{"keyword": "wireless earbuds"}
{"asin": "B09V3KXJPB"}

Returns same product fields as products/search.

5. Realtime Product

Live data for a single ASIN — current listing content and pricing.

POST /openapi/v2/realtime/product
{"asin": "B09V3KXJPB"}

Key response fields:

FieldTypeNote
title, brandStringBasic info
rating, ratingCountFloat/IntRating data
ratingBreakdownObject{five_star: {percentage, count}, ...}
featuresListBullet points
bestsellersRankArray[{category, rank}, ...] — NOT a single integer
buyboxWinnerObject{price, fulfillment, seller} — price is nested here
topReviewsListTop reviews with title, body, rating
variantsListAll variants with dimensions

⚠️ Does NOT return: atLeastMonthlySales, profitMargin, fbaFee, sellerCount. Use products/competitor-lookup for those. ⚠️ Price is nested: buyboxWinner.price, NOT top-level price.

6. Review Analysis

AI-powered consumer insights from customer reviews.

POST /openapi/v2/reviews/analyze

# Single or multiple ASINs (mode + asins required)
{"mode": "asin", "asins": ["B09V3KXJPB"]}
{"mode": "asin", "asins": ["B09V3KXJPB", "B08YYYYY"]}

# Category-level insights
{"mode": "category", "categoryPath": "Pet Supplies,Dogs,Toys", "period": "90d"}

# Filter to specific dimensions
{"mode": "asin", "asins": ["B09V3KXJPB"], "labelType": "painPoints"}

⚠️ mode is required ("asin" or "category"). ⚠️ Use asins (plural, array), NOT asin (singular string).

11 insight dimensions (labelType): painPoints, improvements, buyingFactors, issues, positives, scenarios, keywords, userProfiles, usageTimes, usageLocations, behaviors.

Returns: totalReviews, avgRating, sentimentDistribution, ratingDistribution, consumerInsights, topKeywords, verifiedRatio.

⚠️ Field Differences Across Endpoints

The 4 endpoint types return different fields. Do NOT assume they share the same structure.

Datamarketsproducts/competitorsrealtime/productreviews/analyze
Monthly SalessampleAvgMonthlySales✅ atLeastMonthlySales
PricesampleAvgPricepricebuyboxWinner.price
BSRsampleAvgBsrbsrRank (integer)bestsellersRank (array)
RatingsampleAvgRatingratingratingavgRating
Review CountsampleAvgReviewCountratingCountratingCounttotalReviews
Sentiment✅ sentimentDistribution
Consumer Insights✅ consumerInsights
Pain Points❌ (manual from topReviews)✅ AI-analyzed
Profit MarginprofitMargin
FBA FeefbaFee
Features/Bullets✅ features
VariantsvariantCount (integer)variants (full list)

What Each Endpoint Is Best For

NeedUse This
Sales, pricing, competition dataproducts/search or products/competitor-lookup
Live pricing, reviews, listing contentrealtime/product
Category-level market sizingmarkets/search
Consumer pain points, sentiment, buying factorsreviews/analyze
Category browsing / validationcategories
Full product pictureCombine products (quantitative) + realtime (qualitative) + reviews (insights)

Known Quirks

  1. topN and newProductPeriod are strings — use "10" not 10
  2. listingAge is a string — use "180" not 180
  3. All response .data is an array — use .data[0] not .data.fieldName
  4. ratingCount not reviewCount — the field is called ratingCount everywhere
  5. bsrRank (integer) in products/competitors vs bestsellersRank (array) in realtime
  6. Rate limit: 100 req/min, 10 req/sec burst

Credits

  • Each API call consumes credits
  • Response includes meta.creditsConsumed and meta.creditsRemaining
  • Minimum 50 reviews required for reviews/analyze (returns INSUFFICIENT_REVIEWS error otherwise)
  • Plans & rates: apiclaw.io/pricing

Data Notes

  • Monthly sales (atLeastMonthlySales) is a lower-bound estimate — actual may be higher
  • Realtime vs database: realtime/product is live; products/competitors have ~T+1 delay
  • Currently Amazon US only (amazon.com) — more marketplaces planned
  • Sales estimation fallback: When atLeastMonthlySales is null → Monthly sales ≈ 300,000 / BSR^0.65

Go Deeper

For advanced Amazon product research — 14 selection strategies, risk assessment, pricing analysis, listing optimization, and operational monitoring — install the dedicated skill:

clawhub install Amazon-analysis-skill

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