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apiclaw-core（尖爪核心）

Agent Skill

apiclaw-core 用于查找、检索和筛选相关信息，适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态，以及是否会触发联网、命令执行或文件读写。

总安装

4,396

周安装

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公开资料未说明

下载量

1,539

OpenClaw

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

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-core（尖爪核心）
来源仓库：https://github.com/apiclaw/apiclaw-core
安装命令：
openclaw skills install apiclaw-core
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。

ClawHubOpenClaw

openclaw skills install apiclaw-core

简介

核心 API 集合，包含 11 个关键端点用于商业数据挖掘。

适用于构建自动化选品系统与竞争情报平台。apiclaw-core 属于研究检索类 Skill，可作为该场景下的辅助能力补充。
涵盖类别导航、市场趋势与产品画像等基础功能。
安装命令：openclaw skills install apiclaw-core。
建议配合具体业务需求选择对应端点组合使用。

SKILL.md

name: APIClaw — Amazon Commerce Data, 11 Endpoints
version: 1.1.1
description: >
Endpoints: category browsing, market metrics, product search,
author: SerendipityOneInc
homepage: https://github.com/SerendipityOneInc/APIClaw-Skills
metadata: {"openclaw": {"requires": {"env": ["APICLAW_API_KEY"]}, "primaryEnv": "APICLAW_API_KEY"}}

📋 Live API Reference: Field names and parameters may change. If you encounter field errors, check the latest OpenAPI spec at https://apiclaw.io/api/v1/openapi-spec for current field definitions.

APIClaw — Commerce Data Infrastructure for AI Agents

200M+ Amazon products. 11 endpoints. One API key.

Quick Start

Get key: apiclaw.io/api-keys (1,000 free credits)
export APICLAW_API_KEY='hms_live_xxx'
Base URL: https://api.apiclaw.io/openapi/v2 — all POST with JSON body
Auth: Authorization: Bearer YOUR_API_KEY
New keys need 3-5s to activate. If 403, wait and retry.

⚠️ Critical API Pitfalls (ALL skills must follow)

Keyword search is broad → MUST lock categoryPath first via categories endpoint
Brand/price-band queries MUST include --category to avoid cross-category contamination
Revenue = sampleAvgMonthlyRevenue directly. NEVER calculate avgPrice × totalSales (overestimates 30-70%)
Sales = monthlySalesFloor (lower bound). Fallback: 300,000 / BSR^0.65, tag as 🔍
Use API fields directly: sampleOpportunityIndex, sampleTop10BrandSalesRate — never reinvent
reviews/analysis needs 50+ reviews; fallback to realtime ratingBreakdown
Aggregation endpoints (price-band, brand) without categoryPath produce severely distorted data
Price-band and brand endpoints only accept keyword (not categoryPath) — cross-validate returned products

11 Endpoints

#	Endpoint	Purpose	Key Output
1	`categories`	Browse/search category tree	categoryPath, productCount
2	`markets/search`	Market-level metrics	sampleAvgMonthlySales, sampleAvgPrice, topSalesRate, sampleNewSkuRate
3	`products/search`	Product search (14 modes)	asin, price, monthlySalesFloor, rating, ratingCount, fbaFee
4	`products/competitors`	Competitor discovery	same fields as products/search
5	`realtime/product`	Live ASIN detail	rating, features, bestsellersRank[], buyboxWinner.price, variants
6	`reviews/analysis`	AI review insights (11 dims)	sentimentDistribution, consumerInsights, topKeywords
7	`products/price-band-overview`	Price band summary	hottestBand, bestOpportunityBand, sampleOpportunityIndex
8	`products/price-band-detail`	Full 5-band distribution	priceBands[] with sales, brands, ratings per band
9	`products/brand-overview`	Brand concentration	sampleTop10BrandSalesRate (CR10), sampleBrandCount
10	`products/brand-detail`	Per-brand breakdown	brands[] with sales, revenue, sampleProducts
11	`products/history`	Time series (single ASIN per call)	timestamps[], price[], bsr[], monthlySalesFloor[], rating[], ratingCount[], sellerCount[], title/imageUrl/bestSeller/newRelease/aPlus/inventoryStatus changelogs

Known Quirks

topN, listingAge, newProductPeriod are strings ("10" not 10)
Response .data is always an array — use .data[0]
ratingCount not reviewCount everywhere
bsr (int) in products vs bestsellersRank (array) in realtime
buyboxWinner.price — NOT top-level price in realtime
realtime/product does NOT return: monthlySalesFloor, fbaFee, sellerCount
reviewCountMin/Max filters currently broken (API-56)
reviews/analysis may 500 for certain ASINs (API-58) — retry different ASIN
Rate limit: 100 req/min, 10 req/sec burst
categories uses categoryKeyword (not keyword) and parentCategoryPath (not parentCategoryName)
reviews/analysis: mode required ("asin"/"category"), use asins (plural array) not asin

Field Differences Across Endpoints

Data	markets	products/competitors	realtime	reviews	price-band	brand	history
Sales	sampleAvgMonthlySales	monthlySalesFloor	❌	❌	sampleSalesRate	sampleGroupMonthlySales	monthlySalesFloor[]
Price	sampleAvgPrice	price	buyboxWinner.price	❌	bandMin/MaxPrice	sampleAvgPrice	price[]
BSR	sampleAvgBsr	bsr (int)	bestsellersRank[]	❌	❌	❌	bsr[]
Rating	sampleAvgRating	rating	rating	avgRating	sampleAvgRating	sampleAvgRating	rating[]
Reviews	sampleAvgReviewCount	ratingCount	ratingCount	reviewCount	❌	sampleAvgRatingCount	ratingCount[]
Insights	❌	❌	❌	✅ consumerInsights	❌	❌	❌
Concentration	topSalesRate	❌	❌	❌	sampleTop3BrandSalesRate	CR10	❌
Opportunity	❌	❌	❌	❌	sampleOpportunityIndex	❌	❌

Confidence Labels (all skills)

📊 Data-backed — direct API data
🔍 Inferred — logical reasoning from data
💡 Directional — suggestions, predictions

Strategy recommendations and subjective conclusions are NEVER 📊. Extreme growth (>200%) = 💡 only.

Data Notes

Sales (monthlySalesFloor) = lower-bound estimate
Realtime = live; products/competitors = ~T+1 delay
Amazon US only (amazon.com) — more marketplaces planned
Each call consumes credits; check meta.creditsConsumed

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能力 1

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能力 2

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能力 3

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能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用；具体调用方式请以来源页面和 README 为准。

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敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置，应进入高风险复核队列，默认不自动发布。

安装前确认

本站仅展示第三方公开信息，不托管安装包，不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源，正式发布前建议补源仓库或其他目录站核验。

来源信息

GitHub 仓库

github.com

/apiclaw/apiclaw-core

SKILL.md 来源

clawhub.ai

/apiclaw/apiclaw-core

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