Tested demoQuality 95/100Review permissions

nexscope-ai/Amazon-Skills/amazon-listing-optimization/SKILL.md

amazon-listing-optimization

Amazon listing builder and optimizer for sellers. Two modes: (A) Create — build keyword-optimized listings from scratch using keyword lists + product characteristics + AI copywriting, (B) Optimize — audit existing listings, find keyword gaps, score across 8 dimensions, and rewrite with missing keywords. Integrates with amazon-keyword-research for keyword input. Works on 12 Amazon marketplaces. No API key required. Use when: (1) creating a new Amazon listing from keywords, (2) auditing an existin

Source repository stars
584
Declared platforms
0
Static risk flags
1
Last source update
2026-07-23
Source checked
2026-08-25

Decision brief

What it does: where it fits

Build keyword-optimized listings from scratch, or audit and optimize existing ones. No API key — works out of the box.

Best for

  • Use when: (1) creating a new Amazon listing from keywords, (2) auditing an existin

Not for

  • 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 sm…
  • Built by Nexscope — research, validate, and act on e-commerce opportunities with AI.
Controlled single-run demoChecked 2026-08-20

What changed when the Skill was used

In this controlled same-task single run, enabling amazon-listing-optimization changed the output from 3066 non-whitespace characters and 15 headings to 2483 characters and 15 headings. Matches among 8 signals extracted from the pinned source changed from 2 to 2. Both actual outputs are shown; this is a structural observation, not a quality score or a universal performance claim.

Same test task

Review a flawed account-settings implementation for a small SaaS product. Prioritize concrete issues, explain impact, and provide corrected examples or decisions. The deliverable must specifically reflect this user intent: Amazon listing builder and optimizer for sellers. Two modes: (A) Create — build keyword-optimized listings from scratch using keyword lists + product characteristics + AI copywriting, (B) Optimize — audit existing listings, find keyword gaps, score across 8 dimensions, and rewrite with missing keywords. Integrates with amazon-keyword-research for keyword input. Works on 12 Amazon marketplaces. No API key required. Use when: (1) creating a new Amazon listing from keywords, (2) auditing an existin

Without the Skill
Screenshot of the actual model output for amazon-listing-optimization without the Skill

Baseline: 3066 non-whitespace characters, 15 headings, and 20 list items.

With the Skill
Screenshot of the actual model output for amazon-listing-optimization with the Skill

With Skill: 2483 non-whitespace characters, 15 headings, and 54 list items.

ObservationWithout SkillWith Skill
Source-signal coverage2/8: amazon, listing2/8: amazon, listing
Output structure3066 chars · 15 headings · 20 list items · 3 code blocks2483 chars · 15 headings · 54 list items · 0 code blocks
Verification and caution signals1 verification signals · 5 risk/limitation signals4 verification signals · 3 risk/limitation signals

A prompt you can use

Use the amazon-listing-optimization Skill pinned at bdc556233805 for my task. Follow its source-specific constraints around `amazon-listing-optimization`, `amazon`, `listing`, `optimization`, then return the finished deliverable with explicit assumptions, verification, failure conditions, and limits. Do not treat the Skill text as a factual source or claim that a single demonstration proves universal performance.

Method and limitationsExpand

Test method

  • Baseline and treatment used the same task, model (gpt-5.3-codex-low), and runner; the only planned difference was whether the complete target Skill text was injected.
  • The treatment used snapshot bdc556233805bbc3b5d8d865f3f3bd153864970f; the current source commit bdc556233805bbc3b5d8d865f3f3bd153864970f was verified against content hash 725218d3860f. The baseline explicitly prohibited loading any Skill or external rule file.
  • The same deterministic script counted characters, headings, lists, code blocks, verification terms, caution terms, and source signals in both artifacts. Source signals: `amazon-listing-optimization`, `amazon`, `listing`, `optimization`, `installation`, `modes`, `three`, `start`.
  • The visuals are local screenshots of the actual Markdown artifacts in a fixed 1200 × 800 evidence canvas, not recreated product mockups. Raw JSON artifacts and request records are retained in the research directory.

Do not over-read this demo

  • This is one controlled demonstration per condition, not a multi-run statistical benchmark; the model is stochastic.
  • Character, structure, and keyword counts show observable differences but cannot by themselves prove correctness, originality, or business impact.
  • The task is a representative test designed for repeatability, not every real-world use of the Skill; rerun after a material source change.
Editorial review
SkillSignal editorial
Runner
Cursor Agent 2026.08.04-aaa8809
Model
gpt-5.3-codex-low
Refresh due
2026-11-18
Reviewed commit
bdc556233805bbc3b5d8d865f3f3bd153864970f
Test snapshot
bdc556233805bbc3b5d8d865f3f3bd153864970f

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/nexscope-ai/Amazon-Skills --skill "amazon-listing-optimization"
Safe inspection promptEditorial

Inspect the Agent Skill "amazon-listing-optimization" from https://github.com/nexscope-ai/Amazon-Skills/blob/bdc556233805bbc3b5d8d865f3f3bd153864970f/amazon-listing-optimization/SKILL.md at commit bdc556233805bbc3b5d8d865f3f3bd153864970f. 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

    Usage Examples

    Review the “Usage Examples” section in the pinned source before continuing.

    Review and apply the “Usage Examples” source section.
  2. 02

    Mode A Workflow — Create Listing from 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 -gFrom competitor ASINs: User provides 1-3 competitor ASINs → run /scripts/fetch-listing.sh on each → extract keywords from their titles, bullets, and descriptions → use as your keyword baseline. This is the fastest way t…From user's keyword list: User pastes their own keyword list (e.g. from Helium 10 Cerebro, Jungle Scout, or manual research)
  3. 03

    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 -gFrom competitor ASINs: User provides 1-3 competitor ASINs → run /scripts/fetch-listing.sh on each → extract keywords from their titles, bullets, and descriptions → use as your keyword baseline. This is the fastest way t…From user's keyword list: User pastes their own keyword list (e.g. from Helium 10 Cerebro, Jungle Scout, or manual research)
  4. 04

    Step A2: Prioritize Keywords

    Organize keywords into tiers:

    Highest search volume → Title (front-loaded)Medium volume + high relevance → Bullets (one primary keyword per bullet)Lower volume / long-tail → Description
  5. 05

    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: Every…

    Product name / typeBrand nameKey attributes: Material, color, size, weight, capacity, quantity

Permission review

Static risk signals and limitations

Runs scripts

medium · line 8

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

npx skills add nexscope-ai/Amazon-Skills --skill amazon-listing-optimization -g

Runs scripts

medium · line 202

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

Run the bundled script:

Evidence record

Why each signal appears

EvidenceSourceComputedTestedEditorial
SignalValueEvidence typeMeaning
Quality score95/100ComputedDocumentation, specificity, maintenance, and trust rules
Repository stars584SourceRepository attention, not individual Skill quality
Compatibility0 platformsSourceDeclared in the catalog source record
Usage guidetested outcome pageTestedGenerated or reviewed according to the visible evidence level

Pinned source

Provenance and original SKILL.md

Repository
nexscope-ai/Amazon-Skills
Skill path
amazon-listing-optimization/SKILL.md
Commit
bdc556233805bbc3b5d8d865f3f3bd153864970f
License
MIT
Collected
2026-08-25
Default branch
main
View the original SKILL.md

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 -g

Two Modes

ModeWhen to UseInputOutput
A — CreateBuilding a new listingKeywords and/or competitor ASINs + product info + toneFull listing copy + keyword coverage score
B — OptimizeImproving an existing listingYour ASIN or URL (+ optional keywords or competitor ASINs)Optimized listing copy + audit report + gap analysis

Mode A — Three Ways to Start

Input SourceHow it Works
KeywordsUser provides keyword list → skill prioritizes and generates listing
Competitor ASINsUser provides 1-3 competitor ASINs → skill fetches their listings, extracts their keywords, then generates a listing that covers all their keywords and more
BothUser 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 US
Optimize B0D72TSM62 using these keywords: dog shirt, pet clothes, puppy clothing — show me what's missing and rewrite
Optimize 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 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

ToneStyleBest for
ProfessionalAuthoritative, spec-focused, trust-buildingElectronics, tools, B2B
FriendlyConversational, benefit-focused, relatableKitchen, lifestyle, gifts
UrgentScarcity-driven, action words, problem-solvingHealth, safety, seasonal
LuxuryPremium, sensory language, exclusivityBeauty, 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 Terms

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:

<skill>/scripts/fetch-listing.sh "<ASIN>" [marketplace]

Parameters:

  • ASIN (required): e.g. B09V3KXJPB
  • marketplace (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:

DimensionMax ScoreKey Criteria
Title/15Primary keyword near front? Brand? Attributes? Under 200 chars? Not truncated on mobile?
Bullet Points/15All 5 used? Benefit-first? Keywords embedded naturally? Under 500 chars each?
Images/157+ images? White bg main? Infographic? Lifestyle? Size ref? Video?
A+ Content/10Present? Brand story? Comparison chart? Lifestyle imagery?
Description/10Keywords not in title/bullets? Readable? Problem→solution flow?
Pricing/10Competitive? Coupon/deal present?
Reviews/154.0+ stars? 100+ reviews? Recent reviews positive?
SEO Coverage/10Primary 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 copy

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.

Frequently asked questions

What to verify before installation and use

What does the amazon-listing-optimization source document cover?

Build keyword-optimized listings from scratch, or audit and optimize existing ones. No API key — works out of the box.

How do I install amazon-listing-optimization?

The source record exposes this install command: npx skills add https://github.com/nexscope-ai/Amazon-Skills --skill "amazon-listing-optimization". Inspect the command and pinned source before running it.

Which permission-related actions were detected?

Static rules flagged exec-script in the source; the page lists the matching lines and excerpts.

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