Amazon Listing Optimization 📝
Build keyword-optimized listings from scratch, or audit and optimize existing ones. No API key — works out of the box.
Installation
Two Modes
Mode A — Three Ways to Start
Capabilities
- Keyword-driven listing generation: Import keywords (from amazon-keyword-research, manual list, or extracted from competitor ASINs), rank by priority, generate copy that maximizes keyword coverage
- Competitor keyword extraction: Fetch competitor listings and automatically extract their title/bullet keywords as your baseline
- 8-dimension audit & scoring: Title, bullets, description, images, A+ content, pricing, reviews, SEO coverage
- Keyword coverage tracking: Visual map showing which keywords appear in title / bullets / description / missing
- Tone selection: Professional, Friendly, Urgent, Luxury — affects AI copywriting style
- Competitive benchmarking: Compare your listing against competitors
- Multi-marketplace: US, UK, DE, FR, IT, ES, JP, CA, AU, IN, MX, BR
Usage Examples
Mode A — Create from Keywords
Mode A — Create from Competitor ASINs
Mode A — Create from Keywords + Competitor ASINs
Mode B — Optimize Existing
Mode A Workflow — Create Listing from Keywords
Step A1: Collect Keywords
Keywords can come from four sources (use one or combine multiple):
- From amazon-keyword-research skill (recommended): Run keyword research first, then feed results directly. Install:
npx skills add nexscope-ai/Amazon-Skills --skill amazon-keyword-research -g - From competitor ASINs: User provides 1-3 competitor ASINs → run
<skill>/scripts/fetch-listing.shon each → extract keywords from their titles, bullets, and descriptions → use as your keyword baseline. This is the fastest way to start — you inherit what's already working for competitors, then add more. - From user's keyword list: User pastes their own keyword list (e.g. from Helium 10 Cerebro, Jungle Scout, or manual research)
- Auto-discover: Use
web_searchto find top keywords for the product category
When competitor ASINs are provided, always fetch and analyze them first. Extract every meaningful keyword from their titles and bullets, then merge with any user-provided keywords. The goal: cover everything competitors cover, plus keywords they missed.
Step A2: Prioritize Keywords
Organize keywords into tiers:
Priority rules:
- Highest search volume → Title (front-loaded)
- Medium volume + high relevance → Bullets (one primary keyword per bullet)
- Lower volume / long-tail → Description
- Remaining → Backend search terms (advise seller to add in Seller Central)
Step A3: Collect Product Characteristics
Ask or extract from user input:
- Product name / type
- Brand name
- Key attributes: Material, color, size, weight, capacity, quantity
- Key features: What makes it different (3-5 features)
- Target audience: Who buys this?
- Use cases: Top 3 scenarios
- What's in the box: Everything included
Step A4: Select Tone
Default: Professional if not specified.
Step A5: Generate Listing Copy
Generate each component following these rules:
Title (max 200 characters):
- Format:
[Brand] + [Primary Keyword] + [Key Attribute 1] + [Key Attribute 2] + [Secondary Keyword] + [Differentiator] - Primary keyword as close to the front as possible (after brand)
- No ALL CAPS except brand name
- No promotional claims ("best", "#1", "top rated")
- Include size/color/quantity if relevant to search
Bullet Points (5 bullets, max 500 chars each):
- Each bullet:
[BENEFIT HEADER IN CAPS] — [Benefit explanation with keyword naturally embedded] - Bullet 1: Primary feature + primary keyword
- Bullet 2: Key use case + secondary keyword
- Bullet 3: Quality/material + trust signal
- Bullet 4: What's included / compatibility
- Bullet 5: Guarantee / differentiator / social proof hint
- Each bullet should contain at least 1 target keyword
Description (max 2000 characters):
- Opening: Problem/pain point the product solves
- Middle: Features → benefits (expand on bullets, don't repeat verbatim)
- Close: Call to action + what's in the box
- Embed remaining keywords not used in title/bullets
- Use line breaks for readability
Step A6: Keyword Coverage Score
After generating, produce a coverage map:
Scoring:
- 🟢 90%+ coverage = Excellent
- 🟡 70-89% = Good, minor gaps
- 🔴 <70% = Needs work, significant keywords missing
Mode B Workflow — Optimize Existing Listing
Step B1: Fetch Listing Data
Run the bundled script:
Parameters:
ASIN(required): e.g. B09V3KXJPBmarketplace(optional):us(default),uk,de,fr,it,es,jp,ca,au,in,mx,br
Extracts: Title, brand, price, bullet points, description, image count, A+ content presence, rating, review count, BSR, categories, date first available.
If script returns incomplete data, fall back to web_fetch on the product URL.
Step B2: Discover Target Keywords
If user provides keywords, use those. Otherwise, auto-discover:
- Extract apparent keywords from current title and bullets
- Run
web_searchforsite:amazon.com "[product type]"to find competitors - Extract keywords from top 3 competitor titles and bullets
- (Optional) Chain with
amazon-keyword-researchskill for deeper analysis - Compile a combined keyword list with estimated priority
Step B3: Keyword Gap Analysis
Compare current listing against target keywords:
Step B4: 8-Dimension Audit
Score each on the scale shown, with keyword integration factored in:
Step B5: Generate Optimized Copy
Rewrite the listing incorporating missing keywords:
- Show before vs after for each component
- Highlight which keywords were added and where
- Maintain the brand's existing tone unless a different tone is requested
Output Formats
The primary deliverable is always a ready-to-use listing that the seller can copy-paste directly into Seller Central. Diagnostic data (scores, keyword analysis) comes after as supporting evidence.
Mode A Output — New Listing
Mode B Output — Audit + Optimized Listing
Competitive Comparison (if requested)
Key principles
-
The seller's workflow is: copy the listing → paste into Seller Central → done. The diagnostic section explains WHY those specific words were chosen, but the listing itself must stand alone as a complete, ready-to-use deliverable. Never output only a report without the actual listing copy.
-
Output language must match the target marketplace. Amazon US/UK/AU/CA/IN → English. Amazon DE → German. Amazon FR → French. Amazon JP → Japanese. Amazon ES/MX → Spanish. Amazon IT → Italian. Amazon BR → Portuguese. The entire output (listing copy AND diagnostic section) must be in the marketplace language, regardless of what language the user is speaking in the conversation.
Integration with amazon-keyword-research
This skill works best when chained with amazon-keyword-research:
Limitations
This skill uses publicly available data from Amazon product pages. It cannot access backend search terms, exact search volumes, or PPC/conversion data. For deeper analytics, check out Nexscope — Your AI Assistant for smarter E-commerce decisions.
Built by Nexscope — research, validate, and act on e-commerce opportunities with AI.

