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Agent Skill · 研究检索

amazon-listing-competitor-analysis-skill(亚马逊 listing 竞争对手分析技巧)

amazon-listing-competitor-analysis-skill 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。

amazon-listing-competitor-analysis-skill 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 28,973。

总安装 3,128周安装 133GitHub Stars 公开资料未说明下载 1,096核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

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:amazon-listing-competitor-analysis-skill(亚马逊 listing 竞争对手分析技巧)
来源仓库:https://github.com/browseract-ai/amazon-listing-competitor-analysis-skill
安装命令:
openclaw skills install amazon-listing-competitor-analysis-skill
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 amazon-listing-competitor-analysis-skill

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

这项技能可以帮助用户按 ASIN 分析亚马逊竞争对手的列表,并为其生成结构化的竞争情报和战略机会点。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install amazon-listing-competitor-analysis-skill;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

amazon-listing-competitor-analysis-skill 怎么安装?

在终端执行 openclaw skills install amazon-listing-competitor-analysis-skill。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

amazon-listing-competitor-analysis-skill 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

amazon-listing-competitor-analysis-skill 需要什么权限?

权限级别是接触敏感数据。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。

amazon-listing-competitor-analysis-skill 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

amazon-listing-competitor-analysis-skill 用的人多吗?

公开数据是累计安装 3,128 次,近一周安装 133 次,下载 1,096 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

amazon-listing-competitor-analysis-skill 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
amazon-listing-competitor-analysis-skill

亚马逊 listing 竞争对手分析技巧 · 本页

3,128—接触敏感数据MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
amazon-listing-competitor-analysis-skill
description
This skill helps users analyze Amazon competitor listings by ASIN and produce structured competitive intelligence plus strategic opportunity points for their own go-to-market. The Agent should proactively apply this skill when users want to analyze a competitor Amazon listing by ASIN, understand what a top-ranked product does right in content keywords or visuals, find market gaps and unmet buyer needs, turn competitor research into opportunity maps for their brand, identify keyword placement patterns on rival listings, extract SEO insights from Amazon product pages, reverse-engineer competitor bullet and title strategies, mine competitor reviews for buyer psychology, compare seller and A plus content patterns, run gap analysis before launching a new SKU, research why a listing wins conversion signals, synthesize whitespace you can own versus the diagnosed listing, or say just look at this ASIN with a competitive or optimization angle.
metadata
{"openclaw":{"emoji":"🌐","requires":{"bins":["python"],"env":["BROWSERACT_API_KEY"]}}}

Amazon Listing Competitor Analysis

📖 Brief

This skill runs a two-phase workflow on a single competitor Amazon listing. Phase 1 uses the BrowserAct Amazon Listing Extractor for SEO template to pull visible product data from that listing. Phase 2 diagnoses what that competitor does well and where the market shows gaps, then closes with your strategic opportunity points (how you can win next to them). Do not end with instructions that read like editing or rewriting this competitor's listing; the analyzed ASIN is evidence only. Grounded in extracted data, not generic claims.

✨ Features

  1. No hallucinations, ensuring stable and accurate data extraction: Pre-defined workflows avoid AI-generated hallucinations.
  2. No CAPTCHA issues: No need to handle reCAPTCHA or other verification challenges.
  3. No IP restrictions or geo-blocking: No need to deal with regional IP restrictions.
  4. Faster execution: Task execution is faster compared to pure AI-driven browser automation solutions.
  5. Extremely high cost-efficiency: Significantly reduces data acquisition costs compared to token-heavy AI solutions.

🔑 API Key Guide

Before running, you must check the BROWSERACT_API_KEY environment variable. If it is not set, do not take any other actions; you should request and wait for the user to provide it. The Agent must inform the user:

"Since you haven't configured the BrowserAct API Key yet, please go to the BrowserAct Console to get your Key."

🛠️ Input Parameters

The Agent should dynamically configure the following parameters based on user requirements when calling the script:

  1. ASIN

- Type: string - Description: The ASIN (Amazon Standard Identification Number) of the Amazon product to analyze. - Example: B0CS62LY6P - Required: Yes

  1. Marketplace_url

- Type: string - Description: The base URL of the Amazon marketplace. Use the correct regional site for the listing. - Example: https://www.amazon.com/, https://www.amazon.de/ - Default: https://www.amazon.com/ - Required: No (defaults when omitted)

🚀 Invocation Method

Run Phase 1 extraction with the script below. After structured data is returned, the Agent performs Phase 2 analysis using the framework in Competitive Analysis Framework (Phase 2). The closing section must synthesize opportunity points for the user’s business, not a checklist of edits applied to the competitor page under review.

python -u ./scripts/amazon_listing_competitor_analysis.py "B0CS62LY6P" "https://www.amazon.com/"

When only the ASIN is needed, the marketplace argument may be omitted; the script defaults to https://www.amazon.com/.

⏳ Running Status Monitoring

Since this task involves automated browser operations, it may take a long time (several minutes). The script will continuously output status logs with timestamps (e.g., [14:30:05] Task Status: running) while running. Agent guidelines:

  • While waiting for the script to return a result, please keep monitoring the terminal output.
  • As long as the terminal continues to output new status logs, it means the task is running normally. Do not mistakenly judge it as a deadlock or unresponsiveness.
  • Only consider triggering the retry mechanism if the status remains unchanged for a long time or the script stops outputting without returning a result.

📊 Data Output

Upon successful execution, the script prints the API result string (or full task JSON if no string field is present). Typical fields include:

  • asin, title, product_url, brand, price, coupon_text, rating, review_count, best_sellers_rank, availability, prime_eligible
  • description, short_description, category, key_features, bullet_points
  • main_image_url, additional_image_urls, seller_name, ships_from, sold_by
  • specifications, product_details, attributes, and review-related blocks (reviewer, content, date, helpful votes, etc.)

Use this payload as the single source of truth for Phase 2; do not invent listing facts.

⚠️ Error Handling & Retry

If an error occurs during script execution (such as network fluctuations or task failure), the Agent should follow this logic:

  1. Check the output content:

- If the output contains "Invalid authorization", it means the API Key is invalid or expired. In this case, do not retry. Guide the user to recheck and provide the correct API Key. - If the output contains information related to concurrency limits like "concurrent" or "too many running tasks", it means the concurrent task limit for the current subscription plan has been reached. In this case, do not retry. Guide the user to upgrade their plan. The Agent must inform the user: > "The current task cannot be executed because your BrowserAct account has reached the limit of concurrent tasks. Please go to the BrowserAct Plan Upgrade Page to upgrade your subscription plan and enjoy more concurrent task benefits." - If the output does not contain the above error keywords, but the task fails to execute (e.g., the output starts with Error: or returns an empty result), the Agent should automatically try to execute the script once more.

  1. Retry limit:

- Automatic retry is limited to once. If the second attempt still fails, stop retrying and report the specific error message to the user.

🌟 Typical Use Cases

  1. Competitor listing teardown: Analyze one ASIN to see title formula, bullets, and differentiation language.
  2. Keyword placement audit: Map where primary and long-tail terms appear across title, bullets, and description or A plus content.
  3. Visual strategy review: Infer image narrative, infographic highlights, and video approach from extracted media data.
  4. Buyer-validated selling points: Use high-helpful positive reviews to confirm what buyers value versus what the listing emphasizes.
  5. Unmet needs mining: Use three-star and mixed reviews to find feature and expectation gaps.
  6. Pre-launch gap analysis: Compare a planned positioning against a top competitor's listing structure.
  7. Cross-marketplace research: Run the same ASIN on different regional Amazon URLs for localized copy signals.
  8. Opportunity backlog from a rival listing: Turn extracted facts and gaps into a prioritized map of positioning, search, creative, and offer opportunities for your side of the market.
  9. SEO and conversion benchmarking: Relate BSR, rating volume, and copy patterns without guessing unavailable metrics.
  10. Review-driven objection handling: Surface recurring complaints to address in copy or images.

🧠 Competitive Analysis Framework (Phase 2)

After extraction succeeds, work through each dimension below. Every insight must be grounded in the actual extracted data.

Layer 1 — What the Competitor Did Right

1. Content Strategy

  • Title formula: Information order, primary keyword placement, brand-first vs feature-first vs use-case-first.
  • Bullet priority: What Bullet 1 leads with; selling point order across bullets (signal of tested conversion order).
  • Differentiation language: How generic category features are phrased to sound distinct.
  • A+ content: Modules implied by extracted content (comparison table, brand story, lifestyle, spec callouts).

2. Keyword Placement Strategy

Map *where* terms appear (not only which terms exist):

  • Title (first 80 chars) → primary ranking bets
  • Bullets 1–2 → secondary high-weight terms
  • Bullets 3–5 → long-tail and use-case terms
  • Description / A+ → supplementary terms and synonyms

3. Visual Content Strategy

  • Image narrative arc: Sequence story (hero, lifestyle, pain point, specs, size comparison, social proof, guarantee).
  • Infographic data: Numbers or attributes highlighted and how they are presented.
  • Video (if present in data): Hook length, demo vs lifestyle, subtitles.
  • Overall style: Premium, approachable, technical, lifestyle-focused.

4. Buyer-Validated Selling Points

From four- to five-star reviews with high helpful votes:

  • What reviewers praise that the listing underplays
  • Unexpected benefits buyers mention

Layer 2 — What the Market Lacks

5. Unmet Buyer Needs

From three-star reviews and recurring themes in low stars (non-defect noise):

  • “I wish it had…”, “Would be five stars if…”, “Good but not great because…”

6. Keyword Gaps

  • Natural search terms buyers would use that the listing does not cover
  • High-traffic angles the data suggests but copy does not foreground

7. Visual Content Gaps

  • Weak or missing context in existing images
  • Absent image types (use-case, comparison, real-world scale)

Required Output Format (Phase 2)

Produce the analysis using this structure. Be specific and quote or paraphrase extracted fields and reviews where useful. The final block is your opportunity synthesis; avoid imperatives that sound like “change this competitor's bullet five” or any direct edit list for the ASIN being studied.

Competitor ASIN: [ASIN] | Brand: [brand] | BSR: [rank] | Rating: [x.x] ([N] reviews)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

✅ WHAT THIS COMPETITOR DOES RIGHT

Content Strategy:
  - Title formula: [describe the pattern and keyword placement]
  - Bullet priority: [what each bullet leads with and the logic behind the order]
  - Standout phrasing: [specific language worth noting or borrowing]
  - A+ modules: [which are used and what they emphasize]

Keyword Placement:
  - Primary (title, first 80 chars): [keywords]
  - High-weight (Bullets 1–2): [terms]
  - Long-tail (Bullets 3–5): [terms]
  - Supplementary (description/A+): [terms]

Visual Strategy:
  - Image sequence: [describe the narrative arc across images]
  - Infographic highlights: [what data/specs are called out]
  - Video: [approach if present, or "none"]

Buyer-Validated Selling Points:
  - "[specific insight from high-helpful reviews]"
  - "[another insight]"

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

🕳️ MARKET GAPS (OBSERVED ON THIS COMPETITOR LISTING)

Content gap: [selling points or use cases their copy under-serves, as seen in extracted text]
Keyword gap: [search intents or terms weakly covered on their page — note buyer language from reviews where possible]
Visual gap: [image or video proof types missing or weak on their gallery or A+]
Unmet buyer needs: [recurring themes from 3-star and mixed reviews, quoted or paraphrased]

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

🎯 YOUR STRATEGIC OPPORTUNITY POINTS (FOR YOUR BRAND OR ROADMAP — NOT EDITS TO THIS LISTING)

The ASIN above is the competitor under diagnosis. Below, translate gaps into **where you can win**; do not phrase outcomes as rewriting their bullets or their title.

Positioning and messaging whitespace:
  - [Claim, use case, or audience angle they under-own; why it is an opening for you]

Search and intent capture:
  - [Queries or intents implied by reviews or category that their listing weakly serves; how you could own a different slice of demand]

Trust, proof, and creative differentiation:
  - [Proof points, demos, or gallery angles they lack that you could credibly own]

Product, offer, or bundle opportunity:
  - [Unmet needs from reviews that map to a SKU, variant, bundle, warranty, or service on your side — stay factual to extracted complaints and wishes]

Competitive strengths to respect or neutralize:
  - [What this competitor does so well in copy, visuals, or social proof that you should assume as the bar before claiming superiority]

平台分布

OpenClaw

71.53%
按下载量换算784

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

接触敏感数据

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。目前只有一个公开来源,建议同时核对源仓库。

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