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Amazon Product Research

作者 Kevin Zhang · GitHub ↗ · v0.1.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install amazon-product-research-skill
功能描述
Skill for Amazon product research, market validation, competitor analysis, ASIN review, pricing guidance, and product opportunity discovery. It turns ecommer...
使用说明 (SKILL.md)

Amazon Product Research & Seller Intelligence

A skill for Amazon sellers who need market validation, category analysis, product selection, competitor research, ASIN reviews, pricing guidance, and complete research reports.

It uses APIClaw (apiclaw.io) as its data source, while keeping the focus on structured research workflows and actionable seller decisions.


What this skill is good at

This skill is best for:

  • product discovery: finding promising product opportunities
  • market validation: deciding whether a niche or category is worth entering
  • category analysis: understanding concentration, pricing, brand density, and new-SKU activity
  • competitor research: comparing leading products, brands, and listings
  • ASIN diagnostics: breaking down a specific product in detail
  • pricing and positioning: recommending a launch range and market angle
  • report generation: combining multiple endpoints into a structured market report

Credentials

  • Required credential: APICLAW_API_KEY
  • Purpose: authenticate requests to the APIClaw API
  • Scope: used only for https://api.apiclaw.io
  • No other credentials are required by this skill

Quick start

This skill requires one credential: APICLAW_API_KEY. Create it at APIClaw and configure it before running research workflows.

You can ask questions like:

  1. "Is the pet supplies market worth entering?"
  2. "Analyze ASIN B09V3KXJPB"
  3. "Find Amazon products with low review counts but strong sales"
  4. "Compare the top competitors in this category"
  5. "Generate a full market research report"

File map

Type File When to use it
Main guide SKILL.md Start here for almost every task
Deep-dive modules 01-*.md to 07-*.md Load one module only when the request clearly matches that workflow
Composite workflows workflow-*.md Use when the user wants a complete report or a multi-step research flow
API reference openapi-reference.md Use only when you need exact parameter or response details

Context discipline

  • Start with this file
  • Load only one additional module at a time when possible
  • Use openapi-reference.md only when exact fields or filters matter
  • Prefer fewer, larger, high-value calls over many tiny calls

Intent routing

User request pattern Recommended flow Extra file needed?
Which category has opportunity? Market validation No
Analyze this ASIN ASIN evaluation No
Who are the competitors? Competitor analysis No
What price should I launch at? Pricing & listing No
What are the pain points in reviews? Product evaluation No
Give me a full market report Full market workflow workflow-full-market-report.md
Help me choose products Product selection 02-product-selection.md
Help me expand into adjacent products Expansion 07-expansion.md
Monitor changes over time Daily operations 06-daily-operations.md

Safety and scope

  • This is an instruction-focused research skill
  • It does not install software, request unrelated secrets, or require elevated privileges
  • It uses network access only when the user invokes APIClaw-backed research workflows
  • Its external data dependency is the APIClaw API

API configuration

Item Value
Base URL https://api.apiclaw.io/openapi/v2
Docs https://api.apiclaw.io/api-docs
Auth Authorization: Bearer $APICLAW_API_KEY
Method POST / JSON body
Rate limits 100 requests/min, 10 requests/sec burst
Main marketplace US

Example request

curl -s -X POST "https://api.apiclaw.io/openapi/v2/{endpoint}" \
  -H "Authorization: Bearer $APICLAW_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{ ...params... }'

Endpoint overview

Endpoint Main purpose Best use
categories category tree lookup category discovery and path confirmation
markets/search market-level aggregates market validation and category sizing
products/competitor-lookup competitor set discovery competitor scans and brand comparisons
products/search filtered product search product selection and opportunity screening
realtime/product live product detail ASIN deep dives and listing analysis

Core workflow patterns

1. Market validation

Use:

  • categories → confirm category path
  • markets/search → inspect demand, price, concentration, and new-SKU rate
  • products/search → inspect top products for brand and price structure

Use this when the user asks:

  • "Is this category worth entering?"
  • "Which niche has room?"
  • "Compare these categories"

2. Product discovery

Use:

  • categories → confirm category path if needed
  • products/search → filter for product opportunities
  • realtime/product → validate a shortlist

Use this when the user asks:

  • "Find products for me"
  • "What should I sell?"
  • "Show low-competition opportunities"

3. Competitor analysis

Use:

  • products/competitor-lookup → pull the competitor set
  • realtime/product → inspect leaders in detail

Use this when the user asks:

  • "Analyze competitors"
  • "Compare these listings"
  • "Why is this product winning?"

4. ASIN evaluation

Use:

  • realtime/product → inspect listing, specs, variants, review structure
  • products/competitor-lookup → add market context

Use this when the user asks:

  • "Analyze this ASIN"
  • "Break down this product"
  • "What is weak about this listing?"

5. Pricing and positioning

Use:

  • markets/search → category-level price signals
  • products/search → top product price bands
  • realtime/product → inspect how top listings frame value

Use this when the user asks:

  • "How should I price this?"
  • "What price band makes sense?"
  • "Should I position this as premium or value?"

High-value filters to remember

For markets/search

Most useful fields:

  • sampleAvgMonthlySales
  • sampleAvgMonthlyRevenue
  • sampleAvgPrice
  • sampleAvgReviewCount
  • sampleBrandCount
  • sampleSellerCount
  • sampleFbaRate
  • sampleAmzRate
  • sampleNewSkuRate
  • topSalesRate
  • topBrandSalesRate
  • topSellerSalesRate

For products/search

Most useful filters:

  • monthlySalesMin/Max
  • salesGrowthRateMin/Max
  • priceMin/Max
  • ratingMin/Max
  • reviewCountMin/Max
  • listingAge
  • variantCountMin/Max
  • sellerCountMin/Max
  • includeBrands / excludeBrands
  • fulfillment
  • badges
  • excludeKeywords

Common product-discovery pattern

High demand / low review barrier:

{
  "monthlySalesMin": 300,
  "reviewCountMax": 50,
  "listingAge": "180"
}

Fast-growing products:

{
  "monthlySalesMin": 300,
  "salesGrowthRateMin": 0.1
}

New-product watchlist:

{
  "listingAge": "180",
  "badges": ["New Release"]
}

Reporting guidance

When generating output, prefer a decision-oriented structure:

  1. What the market or product is
  2. What the data suggests
  3. What the main risks are
  4. What the recommendation is
  5. What the next action should be

For reports, include tables such as:

  • top products
  • brand distribution
  • price bands
  • concentration metrics
  • opportunity score breakdown

Recommended next-file loading rules

Load these files only when needed:

  • 01-market-selection.md → category-first and market-entry questions
  • 02-product-selection.md → product shortlisting and discovery
  • 03-competitor-analysis.md → competitor-focused questions
  • 04-product-evaluation.md → single-product or ASIN evaluation
  • 05-pricing-listing.md → pricing and listing strategy
  • 06-daily-operations.md → monitoring and recurring reviews
  • 07-expansion.md → adjacent category or follow-on product ideas
  • workflow-full-market-report.md → complete market report generation
  • workflow-product-opportunity.md → product opportunity shortlisting workflow
  • openapi-reference.md → exact API field and filter reference

Final guidance

This skill is strongest when used for research, evaluation, and decision support. It is not a seller ERP or execution engine. Use it to answer questions such as:

  • What market should I enter?
  • What products should I test?
  • Who are the real competitors?
  • What are the price bands and positioning gaps?
  • What is weak about a specific ASIN?
  • What report should I generate for a seller or team?
安全使用建议
This skill appears to do what it claims: run Amazon research using APIClaw. Before installing, verify APIClaw (https://api.apiclaw.io) is a service you trust, create an API key with minimal privileges if possible, and avoid reusing a high-privilege key. Confirm pricing, data retention, and privacy terms on APIClaw. When using the skill, avoid sharing unrelated sensitive credentials or PII in prompts. If you need higher assurance, test with a limited/test API key and review logs of requests to ensure only expected endpoints are called.
功能分析
Type: OpenClaw Skill Name: amazon-product-research-skill Version: 0.1.0 The skill bundle is a well-structured and comprehensive set of instructions for performing Amazon product research via the APIClaw service. It follows a modular design (01-*.md through 07-*.md) and provides clear guidance for the AI agent to interact with the 'api.apiclaw.io' endpoint using a single required API key. There is no evidence of data exfiltration, malicious execution, or prompt injection intended to subvert the agent's behavior.
能力评估
Purpose & Capability
Name, description, and included workflow files all describe Amazon product/market research and consistently rely on APIClaw endpoints (categories, markets/search, products/search, products/competitor-lookup, realtime/product). The declared credential (APICLAW_API_KEY) and stated base URL match the described purpose.
Instruction Scope
SKILL.md and module files only instruct the agent to call APIClaw endpoints, use provided request templates, and produce reports. There are no instructions to read local files, other environment variables, or to send data to any endpoints beyond api.apiclaw.io.
Install Mechanism
No install specification and no code files — this is instruction-only, so nothing is written to disk or fetched at install time.
Credentials
The skill requires a single credential (APICLAW_API_KEY) which is explicitly scoped and used only for Authorization to https://api.apiclaw.io. No unrelated secrets, binaries, or config paths are requested.
Persistence & Privilege
No privileged flags set (always: false). The skill does not request permanent presence or modify other skills or system settings; it's a normal, user-invocable instruction-only skill.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install amazon-product-research-skill
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /amazon-product-research-skill 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v0.1.0
Version 2.0.0 introduces a new Amazon Product Research & Seller Intelligence skill, powered by APIClaw. - Adds comprehensive Amazon product research workflows: market validation, category analysis, product discovery, competitor analysis, ASIN review, and pricing guidance. - Structured modular documentation with intent-based routing for flexible, use-case driven task execution. - Requires a single credential (`APICLAW_API_KEY`) for secure API access; no other secrets are needed. - Details core endpoints, API call patterns, high-value filters, and best practices for high-impact research. - Guides users with clear workflow patterns and examples for product selection, competitor monitoring, and full market reporting.
元数据
Slug amazon-product-research-skill
版本 0.1.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Amazon Product Research 是什么?

Skill for Amazon product research, market validation, competitor analysis, ASIN review, pricing guidance, and product opportunity discovery. It turns ecommer... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 244 次。

如何安装 Amazon Product Research?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install amazon-product-research-skill」即可一键安装,无需额外配置。

Amazon Product Research 是免费的吗?

是的,Amazon Product Research 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Amazon Product Research 支持哪些平台?

Amazon Product Research 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Amazon Product Research?

由 Kevin Zhang(@kevinzhangqi)开发并维护,当前版本 v0.1.0。

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