A professional diagnostic tool designed to optimize Amazon listings for maximum AI visibility and sales conversion through 5-dimensional analysis.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install amazon-listing-doctor
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install amazon-listing-doctor using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Amazon Listing Doctor?
Amazon Listing Doctor is a specialized utility within the Openclaw Skills ecosystem that provides a comprehensive health check for e-commerce product pages. It specifically targets the new frontier of AI-driven shopping, such as Amazon Rufus, by analyzing how well your content aligns with user intent and usage scenarios rather than just keyword density.
By evaluating five critical pillars—Rufus adaptability, scenario coverage, conversion logic, defensive copy, and visual layout—this tool empowers sellers to transform technical specifications into persuasive, AI-friendly narratives. It is an essential asset for any seller looking to maintain a competitive edge in an increasingly AI-centric marketplace using Openclaw Skills.
Amazon Listing Doctor Use Cases
- Audit existing listings to improve search visibility within the Amazon Rufus AI shopping assistant.
- Refine product titles and bullet points to shift from feature-listing to benefit-driven storytelling.
- Identify gaps in scenario-based keywords to capture high-intent long-tail traffic.
- Implement defensive copywriting strategies to pre-emptively address common customer complaints and reduce return rates.
- Optimize A+ content layout and main image compliance for higher conversion rates.
How Amazon Listing Doctor Works
- Provide the agent with the product category, current title, and the existing five-point bullet description.
- The skill performs a 5-dimensional analysis against industry benchmarks and the Rufus AI intent framework.
- A diagnostic report is generated, assigning a grade (A through D) based on weighted scores across all diagnostic pillars.
- Actionable optimization suggestions are provided for rewriting titles and bullet points with clear before-and-after comparisons.
- The tool suggests specific Rufus-friendly attribute supplements to enhance discoverability in natural language AI dialogues.
Amazon Listing Doctor Setup
To get started with these Openclaw Skills, follow these steps:
# Install the Openclaw CLI if not already present
npm install -g @openclaw/cli
# Add the Amazon Listing Doctor skill to your agent environment
openclaw add amazon-listing-doctor
# Verify the installation and view available triggers
openclaw info amazon-listing-doctor
Amazon Listing Doctor Data Schema & Taxonomy
The skill processes text-based listing data and generates structured Markdown reports with the following taxonomy:
| Component | Description |
|---|---|
| Comprehensive Score | A numerical value (0-100) determining the visibility grade (A-D). |
| Pillar Breakdown | Detailed scores for Rufus Adaptability (30%), Scenario Coverage (25%), and more. |
| Optimization Table | Side-by-side comparison of original text vs. AI-optimized suggestions. |
| Intent Tags | Subjective attributes (e.g., "gift-ready", "beginner-friendly") for AI indexing. |
Amazon Listing Doctor Advanced Features
- Multi-layer analysis capability: Layer 1 for basic diagnostics and Layer 2 for deep scenario keyword matching.
- Defensive Copy Generation: Automatically analyzes category-specific pain points to create preemptive rebuttals in the listing.
- AI Assistant Synergy: Designed to work alongside other Openclaw Skills like Rufus Optimizer and ASIN Clinic for holistic brand management.
- Visual Compliance Auditing: Provides specific feedback on main image photography angles and A+ module selection based on platform best practices.
SKILL.md
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