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browser-act/skills/solutions/ecommerce/amazon-listing-competitor-analysis-skill/SKILL.md

amazon-listing-competitor-analysis-skill

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 pat

Source repository stars
5,155
Declared platforms
0
Static risk flags
2
Last source update
2026-07-21
Source checked
2026-08-04

Decision brief

What it does—and where it fits

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 vi…

Best for

    Not for

    • Tasks that require unconfirmed production actions or broad system permissions.
    • Environments where the pinned source and install steps cannot be inspected.

    Compatibility matrix

    Platform support, with evidence labels

    PlatformStatusEvidenceWhat to check
    CodexNot declaredNo explicit evidencePortability before use
    Claude CodeNot declaredNo explicit evidencePortability before use
    CursorNot declaredNo explicit evidencePortability before use
    Gemini CLINot declaredNo explicit evidencePortability before use
    Open the compatibility checker

    Installation

    Inspect first. Install second.

    The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.

    Source-detected install commandSource
    npx skills add https://github.com/browser-act/skills --skill "solutions/ecommerce/amazon-listing-competitor-analysis-skill"
    Safe inspection promptEditorial

    Inspect the Agent Skill "amazon-listing-competitor-analysis-skill" from https://github.com/browser-act/skills/blob/060f5be942894174722a705b2c450c3e082db379/solutions/ecommerce/amazon-listing-competitor-analysis-skill/SKILL.md at commit 060f5be942894174722a705b2c450c3e082db379. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.

    Workflow

    What the source asks the agent to do

    1. 01

      🧠 Competitive Analysis Framework (Phase 2)

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

      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.
    2. 02

      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…

      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 com…
    3. 03

      📖 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, the…

      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 th…
    4. 04

      ✨ Features

      1. No hallucinations, ensuring stable and accurate data extraction: Pre-set workflows avoid AI generative 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 r…

      No hallucinations, ensuring stable and accurate data extraction: Pre-set workflows avoid AI generative hallucinations.No CAPTCHA issues: No need to handle reCAPTCHA or other verification challenges.No IP restrictions or geo-blocking: No need to deal with regional IP restrictions or geofencing.
    5. 05

      🔑 API Key Guide

      Before running, you must check the BROWSERACTAPIKEY environment variable. If it is not set, do not take other actions first; you should ask and wait for the user to provide it. Agent must inform the user: "Since you haven't configured the BrowserAct API Key yet, please go to the…

      Before running, you must check the BROWSERACTAPIKEY environment variable. If it is not set, do not take other actions first; you should ask and wait for the user to provide it. Agent must inform the user: "Since you hav…

    Permission review

    Static risk signals and limitations

    Runs scripts

    medium · line 35

    The documentation asks the agent to run terminal commands or scripts.

    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 poin

    Network access

    medium · line 38

    The documentation includes network, browsing, or remote request actions.

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

    Runs scripts

    medium · line 38

    The documentation asks the agent to run terminal commands or scripts.

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

    Evidence record

    Why each signal appears

    EvidenceSourceComputedTestedEditorial
    SignalValueEvidence typeMeaning
    Quality score92/100ComputedDocumentation, specificity, maintenance, and trust rules
    Repository stars5,155SourceRepository attention, not individual Skill quality
    Compatibility0 platformsSourceDeclared in the catalog source record
    Usage guideautomated source guideEditorialGenerated or reviewed according to the visible evidence level

    Pinned source

    Provenance and original SKILL.md

    Repository
    browser-act/skills
    Skill path
    solutions/ecommerce/amazon-listing-competitor-analysis-skill/SKILL.md
    Commit
    060f5be942894174722a705b2c450c3e082db379
    License
    MIT
    Collected
    2026-08-04
    Default branch
    main
    View the original SKILL.md

    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. Final narrative output should be grounded in extracted data, not generic claims.

    ✨ Features

    1. No hallucinations, ensuring stable and accurate data extraction: Pre-set workflows avoid AI generative 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 or geofencing.
    4. Faster execution: Tasks execute faster compared to purely AI-driven browser automation solutions.
    5. Extremely high cost-efficiency: Significantly reduces data acquisition costs compared to AI solutions that consume massive amounts of tokens.

    🔑 API Key Guide

    Before running, you must check the BROWSERACT_API_KEY environment variable. If it is not set, do not take other actions first; you should ask and wait for the user to provide it. 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

    When calling the script, the Agent should flexibly configure the following parameters based on user needs:

    1. ASIN

      • Type: string
      • Description: The ASIN (Amazon Standard Identification Number) of the Amazon product to analyze.
      • Example: B0CS62LY6P
      • Required: Yes
    2. 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/

    🚀 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 while running (e.g., [14:30:05] Task Status: running). Agent guidelines:

    • While waiting for the script to return results, please keep an eye on the terminal output.
    • As long as the terminal continues to output new status logs, it means the task is running normally. Do not misjudge it as a deadlock or unresponsiveness.
    • If the status remains unchanged for a long time or the script stops outputting without returning a result, only then consider triggering the retry mechanism.

    📊 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

    During script execution, if errors occur (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. At this point, do not retry, but guide the user to recheck and provide the correct API Key.
      • If the output contains "concurrent" or "too many running tasks" or similar concurrency limit messages, it means the concurrent task limit for the current subscription plan has been reached. Do not retry; guide the user to upgrade their plan. 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 (e.g., output starts with Error: or returns empty results), the Agent should automatically try to run the script once more.
    2. 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+ 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]
    

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