
Amazon Listing Optimization
- 1k installs
- 480 repo stars
- Updated July 23, 2026
- nexscope-ai/amazon-skills
amazon-listing-optimization is a Claude Code ecommerce skill that creates or audits Amazon product listings with keyword optimization across 12 marketplaces for developers and sellers who need higher-ranking, higher-conv
About
amazon-listing-optimization is a Claude Code skill from nexscope-ai/amazon-skills with two modes: Create builds keyword-optimized listings from keyword lists and product characteristics, and Optimize audits existing listings across 8 scoring dimensions, finds keyword gaps, and rewrites copy with missing terms. The skill works on 12 Amazon marketplaces and integrates with amazon-keyword-research for keyword input while requiring no API key. Sellers and ecommerce developers reach for amazon-listing-optimization when launching a new ASIN or auditing title, bullet, and description keyword coverage for SEO and conversion. Output includes scored audits and rewritten listing copy aligned to target keywords.
- Two distinct modes: Create new keyword-optimized listings from scratch or Optimize existing ones
- Audits listings across 8 scoring dimensions and surfaces keyword gaps
- Integrates directly with amazon-keyword-research skill for seamless keyword input
- Supports all 12 Amazon marketplaces with no API key required
- Generates full listing copy including title, bullets, description with target tone and keywords
Amazon Listing Optimization by the numbers
- 1,030 all-time installs (skills.sh)
- +80 installs in the week ending Aug 2, 2026 (Skillselion tracking)
- Ranked #441 of 1,879 Marketing & SEO skills by installs in the Skillselion catalog
- Data as of Aug 3, 2026 (Skillselion catalog sync)
npx skills add https://github.com/nexscope-ai/amazon-skills --skill amazon-listing-optimizationAdd your badge
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| Installs | 1k |
|---|---|
| repo stars | ★ 480 |
| Last updated | July 23, 2026 |
| Repository | nexscope-ai/amazon-skills ↗ |
How do you optimize Amazon listing keywords for conversion?
Generate or improve Amazon product listings that rank higher and convert better using built-in keyword optimization.
Who is it for?
Amazon sellers and ecommerce developers who need keyword-driven listing creation or audits across multiple marketplaces without connecting Seller Central APIs.
Skip if: Developers building Shopify or generic ecommerce sites, or teams that only need Amazon PPC ad management without listing copy work.
When should I use this skill?
The user asks to create a new Amazon listing from keywords, audit listing SEO, check keyword coverage, or rewrite product copy for Amazon marketplaces.
What you get
Keyword-optimized listing copy, 8-dimension audit scores, and gap reports for title, bullets, and description fields.
- Keyword-optimized Amazon listing copy
- 8-dimension audit score report
- Keyword gap analysis
By the numbers
- Supports 12 Amazon marketplaces
- Optimize mode scores listings across 8 dimensions
- Two modes: Create and Optimize
Files
Amazon Listing Optimization 📝
Build keyword-optimized listings from scratch, or audit and optimize existing ones. No API key — works out of the box.
Installation
npx skills add nexscope-ai/Amazon-Skills --skill amazon-listing-optimization -gTwo Modes
| Mode | When to Use | Input | Output |
|---|---|---|---|
| A — Create | Building a new listing | Keywords and/or competitor ASINs + product info + tone | Full listing copy + keyword coverage score |
| B — Optimize | Improving an existing listing | Your ASIN or URL (+ optional keywords or competitor ASINs) | Optimized listing copy + audit report + gap analysis |
Mode A — Three Ways to Start
| Input Source | How it Works |
|---|---|
| Keywords | User provides keyword list → skill prioritizes and generates listing |
| Competitor ASINs | User provides 1-3 competitor ASINs → skill fetches their listings, extracts their keywords, then generates a listing that covers all their keywords and more |
| Both | User provides keywords + competitor ASINs → skill merges both sources for maximum coverage |
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
Create a listing for a portable blender. Keywords: portable blender, smoothie maker, USB rechargeable, travel blender, personal blender. Material: BPA-free Tritan. Color: White. Capacity: 380ml. Tone: Friendly.I have these keywords from my research: [paste keyword list]. Product: silicone kitchen utensil set, 12 pieces, heat resistant to 480°F. Generate a full listing.Mode A — Create from Competitor ASINs
I want to sell a dog t-shirt on Amazon US. Here are 3 competitors I want to beat: B0D72TSM62, B0ABC12345, B0XYZ67890. My product is 100% cotton, 6 colors, XS-XL, funny print. Analyze their listings and create one that's better. Friendly tone.Create a listing for my yoga mat. Look at this competitor: B09V3KXJPB. Extract their keywords, find what they're missing, and build a listing that covers more keywords than them. Product: 6mm TPE, non-slip, carrying strap included. Tone: Professional.Mode A — Create from Keywords + Competitor ASINs
Use amazon-keyword-research to find keywords for "portable blender", also analyze these competitors: B0CPY1GFVZ, B0CXLF3Y19. Combine all keywords and create a listing. Product: 380ml, USB-C, BPA-free Tritan. Tone: Professional.Mode B — Optimize Existing
Audit the listing for ASIN B0D72TSM62 on Amazon USOptimize B0D72TSM62 using these keywords: dog shirt, pet clothes, puppy clothing — show me what's missing and rewriteOptimize my listing B0D72TSM62 by analyzing these competitors: B0ABC12345, B0XYZ67890. Find what keywords they have that I don't, and rewrite my listing to beat them.---
Mode A Workflow — Create Listing from Keywords
Step A1: Collect Keywords
Keywords can come from four sources (use one or combine multiple):
1. From [amazon-keyword-research](https://github.com/nexscope-ai/Amazon-Skills/tree/main/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 2. From competitor ASINs: User provides 1-3 competitor ASINs → run <skill>/scripts/fetch-listing.sh on 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. 3. From user's keyword list: User pastes their own keyword list (e.g. from Helium 10 Cerebro, Jungle Scout, or manual research) 4. Auto-discover: Use web_search to 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:
🔴 Primary (must appear in Title):
- [keyword] — [search volume if known]
- [keyword] — [search volume if known]
🟡 Secondary (must appear in Bullets):
- [keyword]
- [keyword]
🟢 Tertiary (should appear in Description or Backend):
- [keyword]
- [keyword]
⚪ Long-tail (use where natural):
- [keyword phrase]
- [keyword phrase]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
| Tone | Style | Best for |
|---|---|---|
| Professional | Authoritative, spec-focused, trust-building | Electronics, tools, B2B |
| Friendly | Conversational, benefit-focused, relatable | Kitchen, lifestyle, gifts |
| Urgent | Scarcity-driven, action words, problem-solving | Health, safety, seasonal |
| Luxury | Premium, sensory language, exclusivity | Beauty, fashion, premium goods |
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:
## Keyword Coverage Report
| Keyword | Volume | In Title? | In Bullets? | In Description? | Status |
|---------|--------|-----------|-------------|-----------------|--------|
| portable blender | 45,000 | ✅ | ✅ | ✅ | 🟢 Covered |
| smoothie maker | 22,000 | ❌ | ✅ | ✅ | 🟡 Add to title |
| USB rechargeable | 18,000 | ✅ | ✅ | ❌ | 🟢 Covered |
| travel blender | 12,000 | ❌ | ❌ | ✅ | 🟡 Add to bullets |
| mini blender | 8,000 | ❌ | ❌ | ❌ | 🔴 Missing |
Coverage: 18/22 keywords (82%)
Title keywords: 6/8 slots used
Bullet keywords: 12/15 target keywords covered
Uncovered → recommend for Backend Search TermsScoring:
- 🟢 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:
<skill>/scripts/fetch-listing.sh "<ASIN>" [marketplace]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:
1. Extract apparent keywords from current title and bullets 2. Run web_search for site:amazon.com "[product type]" to find competitors 3. Extract keywords from top 3 competitor titles and bullets 4. (Optional) Chain with amazon-keyword-research skill for deeper analysis 5. Compile a combined keyword list with estimated priority
Step B3: Keyword Gap Analysis
Compare current listing against target keywords:
## Keyword Gap Analysis: [ASIN]
### ✅ Keywords Found in Listing
| Keyword | In Title | In Bullets | In Description |
|---------|----------|------------|----------------|
| [kw] | ✅ | ✅ | ❌ |
### ❌ Missing Keywords (Competitors Have, You Don't)
| Keyword | Competitor 1 | Competitor 2 | Competitor 3 | Priority |
|---------|-------------|-------------|-------------|----------|
| [kw] | ✅ Title | ✅ Bullet | ❌ | 🔴 High |
### Coverage: X/Y keywords (Z%)Step B4: 8-Dimension Audit
Score each on the scale shown, with keyword integration factored in:
| Dimension | Max Score | Key Criteria |
|---|---|---|
| Title | /15 | Primary keyword near front? Brand? Attributes? Under 200 chars? Not truncated on mobile? |
| Bullet Points | /15 | All 5 used? Benefit-first? Keywords embedded naturally? Under 500 chars each? |
| Images | /15 | 7+ images? White bg main? Infographic? Lifestyle? Size ref? Video? |
| A+ Content | /10 | Present? Brand story? Comparison chart? Lifestyle imagery? |
| Description | /10 | Keywords not in title/bullets? Readable? Problem→solution flow? |
| Pricing | /10 | Competitive? Coupon/deal present? |
| Reviews | /15 | 4.0+ stars? 100+ reviews? Recent reviews positive? |
| SEO Coverage | /10 | Primary kw in title+bullets+desc? Long-tail present? No wasted repeats? Keyword coverage % |
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
# ✅ Your Listing — Ready to Use
## Title
[title text — copy this directly into Seller Central]
## Bullet Points
1. [BENEFIT HEADER] — [text with keyword]
2. [BENEFIT HEADER] — [text with keyword]
3. [BENEFIT HEADER] — [text with keyword]
4. [BENEFIT HEADER] — [text with keyword]
5. [BENEFIT HEADER] — [text with keyword]
## Description
[description text — copy this directly into Seller Central]
## Backend Search Terms
[comma-separated keywords to paste into Seller Central → Keywords → Search Terms]
---
# 📊 How We Built This Listing (Diagnostic)
**Marketplace:** Amazon [XX] | **Tone:** [tone] | **Keywords imported:** [count]
**Title characters:** [X]/200 | **Description characters:** [X]/2000
## Keyword Coverage: [X]%
| Keyword | Volume | In Title | In Bullets | In Description | Status |
|---------|--------|----------|------------|----------------|--------|
| [kw] | [vol] | ✅/❌ | ✅/❌ | ✅/❌ | 🟢🟡🔴 |
## Keyword Priority Breakdown
🔴 Primary (Title): [list]
🟡 Secondary (Bullets): [list]
🟢 Tertiary (Description): [list]
⚪ Backend: [list]Mode B Output — Audit + Optimized Listing
# ✅ Optimized Listing — Ready to Use
## Title
[optimized title — copy this directly into Seller Central]
## Bullet Points
1. [BENEFIT HEADER] — [optimized text]
2. [BENEFIT HEADER] — [optimized text]
3. [BENEFIT HEADER] — [optimized text]
4. [BENEFIT HEADER] — [optimized text]
5. [BENEFIT HEADER] — [optimized text]
## Description
[optimized description — copy this directly into Seller Central]
## Backend Search Terms
[comma-separated keywords to paste into Seller Central → Keywords → Search Terms]
---
# 📊 Audit Report: [ASIN]
**Product:** [title] | **Brand:** [brand]
**Price:** [price] | **Rating:** [stars] ([count] reviews)
## Score: [X/100] → [Y/100] (after optimization)
| Dimension | Before | After | Key Change |
|-----------|--------|-------|-----------|
| Title | /15 | /15 | [what changed] |
| Bullet Points | /15 | /15 | [what changed] |
| Images | /15 | — | [recommendation only] |
| A+ Content | /10 | — | [recommendation only] |
| Description | /10 | /10 | [what changed] |
| Pricing | /10 | — | [observation] |
| Reviews | /15 | — | [observation] |
| SEO Coverage | /10 | /10 | [what changed] |
## Keyword Coverage: [X]% → [Y]%
| Keyword | Before | After | Where Added |
|---------|--------|-------|-------------|
| [kw] | ❌ | ✅ | Title + Bullet 2 |
| [kw] | ✅ Title only | ✅ Title + Bullets | Bullet 4 |
## What Changed (Before → After)
**Title:**
> ❌ [original]
> ✅ [optimized]
**Bullets:**
> ❌ 1. [original]
> ✅ 1. [optimized — added: +[kw1], +[kw2]]
## 🔴 Issues Fixed
1. [what was wrong → how we fixed it]
## 🟡 Recommendations (requires seller action)
1. [image improvements, A+ content, pricing — things the skill can't rewrite]
## 🟢 What Was Already Working
1. [positive aspects preserved]Competitive Comparison (if requested)
| Dimension | Your Listing | Competitor 1 | Competitor 2 | Competitor 3 |
|-----------|-------------|-------------|-------------|-------------|
| Title score | /15 | /15 | /15 | /15 |
| Bullets score | /15 | /15 | /15 | /15 |
| Images | [count] | [count] | [count] | [count] |
| A+ Content | Yes/No | Yes/No | Yes/No | Yes/No |
| Keyword coverage | X% | X% | X% | X% |
| Price | — | — | — | — |
| Rating | — | — | — | — |
| **Total** | **/100** | **/100** | **/100** | **/100** |Key principles
1. 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.
2. 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:
Step 1: "Research keywords for portable blender on Amazon US"
→ amazon-keyword-research returns keyword list with volumes
Step 2: "Now create a listing using those keywords. Product: 380ml BPA-free blender, USB-C rechargeable. Tone: Friendly."
→ amazon-listing-optimization Mode A uses the keywords to generate optimized copyLimitations
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](https://www.nexscope.ai/?co-from=skill) — Your AI Assistant for smarter E-commerce decisions.
---
Built by [Nexscope](https://www.nexscope.ai/?co-from=skill) — research, validate, and act on e-commerce opportunities with AI.
{
"name": "amazon-listing-optimization",
"version": "1.0.0",
"ownerId": "nexscope-ai"
}
#!/usr/bin/env bash
# Amazon Listing Fetcher — extracts listing data from an Amazon product page
# Usage: fetch-listing.sh <ASIN> [marketplace]
# Marketplaces: us (default), uk, de, fr, it, es, jp, ca, au, in, mx, br
set -uo pipefail
ASIN="${1:?Usage: fetch-listing.sh <ASIN> [marketplace]}"
MP="${2:-us}"
declare -A DOMAINS=(
[us]="www.amazon.com" [uk]="www.amazon.co.uk" [de]="www.amazon.de"
[fr]="www.amazon.fr" [it]="www.amazon.it" [es]="www.amazon.es"
[jp]="www.amazon.co.jp" [ca]="www.amazon.ca" [au]="www.amazon.com.au"
[in]="www.amazon.in" [mx]="www.amazon.com.mx" [br]="www.amazon.com.br"
)
DOMAIN="${DOMAINS[$MP]:-www.amazon.com}"
URL="https://${DOMAIN}/dp/${ASIN}"
# Fetch the page
PAGE=$(curl -sL \
-H "User-Agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36" \
-H "Accept-Language: en-US,en;q=0.9" \
-H "Accept: text/html,application/xhtml+xml" \
--max-time 15 \
"$URL" 2>/dev/null)
if [ -z "$PAGE" ]; then
echo "ERROR: Failed to fetch $URL"
exit 1
fi
echo "=== LISTING DATA FOR $ASIN ($MP) ==="
echo "URL: $URL"
echo ""
# Title
echo "=== TITLE ==="
echo "$PAGE" | grep -o 'productTitle"[^>]*>[^<]*' | sed 's/productTitle"[^>]*>//;s/^[[:space:]]*//;s/[[:space:]]*$//' | head -1
echo ""
# Brand
echo "=== BRAND ==="
echo "$PAGE" | grep -o 'bylineInfo"[^>]*>[^<]*' | sed 's/bylineInfo"[^>]*>//;s/^[[:space:]]*Visit the //;s/ Store$//' | head -1
echo ""
# Price
echo "=== PRICE ==="
echo "$PAGE" | grep -o '<span class="a-offscreen">[^<]*</span>' | head -1 | sed 's/<[^>]*>//g'
echo ""
# Rating
echo "=== RATING ==="
echo "$PAGE" | grep -o '[0-9]\.[0-9] out of 5 stars' | head -1
echo ""
# Review count
echo "=== REVIEW COUNT ==="
echo "$PAGE" | grep -o 'acrCustomerReviewText"[^>]*>[^<]*' | sed 's/acrCustomerReviewText"[^>]*>//' | head -1
echo ""
# Bullet points
echo "=== BULLET POINTS ==="
echo "$PAGE" | grep -o 'a-list-item">[A-Z][^<]\{15,\}' | sed 's/a-list-item">//' | head -10
echo ""
# Description
echo "=== DESCRIPTION ==="
echo "$PAGE" | grep -o 'productDescription"[^>]*>.*</div>' | head -1 | sed 's/<[^>]*>//g;s/^[[:space:]]*//;s/[[:space:]]*$//' | head -5
echo ""
# Image count (main images)
echo "=== IMAGE COUNT ==="
IMG_COUNT=$(echo "$PAGE" | grep -o '"hiRes":"https://[^"]*"' | wc -l)
echo "$IMG_COUNT main images"
echo ""
# A+ Content detection
echo "=== A+ CONTENT ==="
if echo "$PAGE" | grep -q 'aplus-v2\|a-plus-content\|aplusPageWidget'; then
echo "YES — A+ Content detected"
else
echo "NO — No A+ Content found"
fi
echo ""
# BSR
echo "=== BEST SELLERS RANK ==="
echo "$PAGE" | grep -o '#[0-9,]* in [^<]*' | head -3
echo ""
# Category
echo "=== CATEGORY ==="
echo "$PAGE" | grep -o 'a-link-normal a-color-tertiary"[^>]*>[^<]*' | sed 's/.*>//;s/^[[:space:]]*//;s/[[:space:]]*$//' | head -5
echo ""
# Date first available
echo "=== DATE FIRST AVAILABLE ==="
echo "$PAGE" | grep -o 'Date First Available[^<]*' | sed 's/Date First Available//;s/[^A-Za-z0-9, ]//g;s/^[[:space:]]*//;s/[[:space:]]*$//' | head -1
echo ""
echo "=== END ==="
Related skills
FAQ
What modes does amazon-listing-optimization provide?
amazon-listing-optimization offers Create mode to build keyword-optimized listings from keyword lists and product traits, and Optimize mode to audit existing listings across 8 dimensions, surface keyword gaps, and rewrite copy with missing terms.
Does amazon-listing-optimization need an Amazon API key?
amazon-listing-optimization requires no API key and works across 12 Amazon marketplaces. Keyword input can flow from the companion amazon-keyword-research skill for research-driven listing builds.