nexscope-ai/ecommerce-skills/product-description-generator
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E-commerce product description generator for any platform. Generates optimized titles, bullet points, descriptions, and backend keywords using competitor research + keyword scoring + FABE copywriting. Two modes: (A) Create — generate listing from product specs with optional competitor analysis, (B) Optimize — improve existing listing with keyword gap analysis. Supports Amazon, eBay, Walmart, Shopify, Etsy, TikTok Shop, Lazada, Shopee. No API key required. Use when: (1) writing a new product listing, (2) analyzing what makes competitors rank, (3) improving an underperforming listing.
Install
npx vskill@latest install nexscope-ai/ecommerce-skills/product-description-generatorSKILL.md
Product Description Generator 📝
Generate platform-optimized product copy — titles, bullet points, descriptions, and backend keywords — for any major e-commerce platform. No API key required.
Installation
For Amazon listings, use our dedicated skill with Cosmo algorithm optimization:```bashnpx skills add nexscope-ai/Amazon-Skills --skill amazon-listing-optimization -g```
Two Modes
| Mode | When to Use | Input | |
|---|---|---|---|
| A — Create | Writing a new listing | Product specs + optional competitor URLs | |
| B — Optimize | Improving existing listing | Current listing or URL + optional competitor URLs |
Both modes support competitor analysis — just include competitor URLs to enable it.
Supported Platforms
| Platform | Output Components | |
|---|---|---|
| Amazon | Title (≤200) + 5 Bullets (≤500 each) + Description (≤2000) + Backend (≤250 bytes) | |
| eBay | Title (≤80) + HTML Description | |
| Walmart | Title (≤75) + Short Desc (≤150) + 10 Features + Long Desc | |
| Shopify/DTC | SEO Title (≤60) + Meta Desc (≤160) + Product Description | |
| Etsy | Title (≤140) + Description + 13 Tags (≤20 each) | |
| TikTok Shop | Title (≤255) + Description (≤1000) | |
| Lazada/Shopee | Title (≤120) + 5 Highlights + Description |
Usage Examples
Mode A — Create
Mode B — Optimize
Handling Incomplete Input
If user doesn't provide enough info, ask upfront:
Mode A Workflow — Create New Listing
Step 1: Collect Product Info
| Field | Required | Example | |
|---|---|---|---|
product_name | ✅ | Portable blender | |
platform | ✅ | Etsy | |
brand | ✅ | BlendJet | |
key_features | ✅ | USB-C, 6 blades, BPA-free | |
specs | ✅ | 380ml, 175W motor | |
target_audience | 👍 | Gym-goers, travelers | |
use_cases | 👍 | Smoothies, protein shakes | |
competitor_urls | 👍 | 1-3 URLs to analyze | |
tone | Optional | Professional (default) / Friendly / Luxury / Urgent |
Step 2: Gather Keywords
If competitor URLs provided:
- Fetch each competitor page:
`` Use web_fetch on each competitor URL. Extract: title, bullets/features, description, price, review count, brand name. ``
- If
web_fetchfails or returns incomplete data:
`` Fallback: web_search for "[product title from URL]" site:[platform].com Extract data from search snippets. ``
- Parse competitor content and extract keywords in these categories:
- Product-type terms: What it IS (yoga mat, exercise mat)
- Feature terms: What it DOES (non-slip, eco-friendly)
- Use-case terms: WHERE/WHEN used (home gym, yoga studio)
- Audience terms: WHO buys (beginners, athletes)
- Attribute terms: Specs (6mm, TPE material)
- Expand beyond competitors:
`` web_search: "[product type]" best seller features what buyers want web_search: "[product type]" review complaints common issues web_search: site:[platform].com "[product type]" ``
If no competitor URLs provided:
- Discover keywords via web search:
`` web_search: "[product name]" best seller [platform] features web_search: "[product name]" review what customers love web_search: "[product name]" vs alternatives comparison web_search: site:[platform].com "[product name]" ``
- Extract keywords from top 5 results following the same categories above.
⚠️ Critical: Remove all competitor brand names — never include them in output.
Step 3: Score and Prioritize Keywords
Score each keyword (1-9 points):
| Dimension | Scoring | |
|---|---|---|
| Frequency | In 3+ competitor titles = 3 pts / In 1-2 = 2 pts / Bullets only = 1 pt | |
| Relevance | Core descriptor = 3 pts / Feature = 2 pts / Peripheral = 1 pt | |
| Opportunity | Few competitors use = 3 pts / Most use = 2 pts / All use = 1 pt |
Assign to tiers:
Step 4: Generate Copy
Proceed to Generate Copy section.
Mode B Workflow — Optimize Existing Listing
Step 1: Analyze Current Listing
User may provide:
- Full listing copy (title, bullets, description pasted directly)
- Product URL (e.g.,
https://www.etsy.com/listing/123456) - Platform + product identifier (e.g., "Etsy listing 123456")
If user provides URL or identifier only:
If web_fetch fails:
Once listing content is obtained, parse and extract:
- All keywords currently present
- Structure and format used
- Obvious gaps (missing features, weak benefits, no FABE structure)
Step 2: Gather Target Keywords
If competitor URLs provided:
Follow the same competitor analysis process as Mode A Step 2:
web_fetcheach competitor URL- Extract their keywords
- Expand via web search
If no competitor URLs provided:
Discover ideal keywords for the product type:
Step 3: Gap Analysis
Compare current keywords vs. target keywords:
Step 4: Rewrite
Generate optimized copy incorporating missing keywords.
Show Before → After for each component.
Proceed to Generate Copy section.
Generate Copy
Final step for all modes after keyword priority table is built.
Writing Framework: FABE
Apply to every bullet:
Lead with the Benefit — customers buy outcomes, not features.
Example:
Platform-Specific Writing Rules
Amazon (Cosmo Algorithm)
- Title: Brand + Primary Keyword + Attribute + Attribute + Secondary Keyword, ≤200 chars
- Bullets: [CAPS HEADER] — Benefit-led sentence with 1-2 keywords embedded
- Description: Hook → Features → Use cases → What's in box → CTA
- Backend: Space-separated keywords, no duplicates, ≤250 bytes
- ⚠️ Cosmo tip: Use situational language (when/where/why), cover multiple use cases
- 💡 For advanced Amazon optimization, consider amazon-listing-optimization
eBay (Cassini Algorithm)
- Title: Front-load exact-match keywords, 80 chars max
- Description: Repeat top 3 keywords naturally throughout, include specs table in HTML
Walmart
- Title: Brand + product name + primary attribute, ≤75 chars
- Short Desc: One-sentence value prop with primary keyword
- Features: 10 attribute-focused bullets, one fact per bullet
Shopify/DTC (Google SEO)
- SEO Title: Primary keyword + brand, written for Google (not just product name)
- Meta Desc: Keyword + benefit + CTA, drives CTR from search results
- Description: Storytelling structure with
<h2>,<ul>,<strong>for on-page SEO
Etsy (Tag Matching)
- Title: Long-tail keyword phrase first, then style/material/occasion
- Description: Conversational, first 160 chars = meta description
- Tags: 13 tags (≤20 chars each), match phrases used in title exactly
TikTok Shop (Social Commerce)
- Title: Lead with problem or desire ("Tired of X?") → product → top feature
- Description: Hook → pain point → solution → 3 bullets → CTA. Conversational, emoji-friendly.
Lazada/Shopee
- Title: Brand + product + model + material + key attribute (completeness over cleverness)
- Highlights: 5 short bullets, one feature per line, spec-focused
- Description: Feature table + expanded use cases
Tone Guide
| 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.
Output Format
Integration with Other Skills
This is the start of the file. Read the full SKILL.md on GitHub.
Security
- Security scanPassed, 100 of 100Pattern checks on the skill's files.
- Model reviewNot runA model review is scheduled for the next rescan.
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingproduct-description-generator/SKILL.md
Popularity
- Repository stars
- 612
- Repository forks
- 90
- 7-day trend score
- 32
Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 7 Aug 2026, 2 months ago.
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