A professional research tool designed to generate authentic, anti-shill analysis reports for smart pet technology products.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install pet-product-analysis
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 pet-product-analysis 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 Pet Product Analysis AI Assistant?
This skill provides a specialized framework for analyzing high-tech pet products such as smart cat litter boxes, automatic feeders, and pet cameras. By leveraging Openclaw Skills, it synthesizes official technical specifications with raw user feedback gathered from social platforms like Xiaohongshu and Bilibili. The primary goal is to provide a transparent look at product performance while actively filtering out marketing hype and sponsored soft ads.
The tool is essential for developers and consumers who need deep-dive technical comparisons, safety evaluations, and long-term maintenance cost analysis. It moves beyond surface-level reviews by applying a structured logic that weighs noise control, sensor reliability, and app connectivity, resulting in a data-driven score for every product analyzed.
Pet Product Analysis AI Assistant Use Cases
- Creating comprehensive buying guides for smart pet appliances.
- Conducting competitive landscape research for pet hardware startups.
- Generating unbiased review content for tech blogs or pet-focused communities.
- Evaluating the safety and multi-pet compatibility of automated litter solutions.
How Pet Product Analysis AI Assistant Works
- Initialize the analysis by defining the target product name, type, and specific focus areas like budget or safety.
- Fetch official technical parameters including dimensions, material certifications, and power specifications.
- Identify and gather data for 3-5 primary competitors to create a cross-functional comparison matrix.
- Search social media platforms using specific long-tail keywords to extract real-world user experiences.
- Filter results through an anti-shill algorithm that flags suspicious linguistic patterns, high follower counts, and lack of critical feedback.
- Multi-dimensionally analyze the data based on specific category frameworks (e.g., noise, cleaning efficiency, or dispensing accuracy).
- Produce a structured Markdown report featuring source-verified pros and cons and a final weighted score.
Pet Product Analysis AI Assistant Setup
To get started with this skill within your environment, use the following commands:
# Install the pet product analysis skill
openclaw install pet-product-analysis
# Configure your search environment for platform access
export OPENCLAW_SEARCH_ENABLED=true
Ensure your agent has network access to perform deep-web searches on tech specifications and social review sites.
Pet Product Analysis AI Assistant Data Schema & Taxonomy
The skill organizes its output into a structured report using the following data taxonomy:
| Section | Data Included | Format |
|---|---|---|
| Product Overview | Specs, pricing, core selling points | Markdown Table |
| Competitor Matrix | Comparative analysis of 3-5 rival products | Markdown Table |
| Verified Reviews | Source-linked pros and cons from real users | Unordered List |
| Dimensional Analysis | Ratings for safety, noise, and app stability | Star Rating |
| Final Recommendation | Targeted advice for different user personas | Markdown Text |
Pet Product Analysis AI Assistant Advanced Features
- Advanced Sponsored Content Detection: Automatically filters out marketing fluff and shills using fan-count thresholds and sentiment analysis.
- Platform-Specific Scrapers: Deep integration with Bilibili for video review summaries and Xiaohongshu for lifestyle feedback.
- Category-Aware Frameworks: Dynamically switches analysis logic between different hardware types (e.g., checking for 'clumping' in litter boxes vs. 'jamming' in feeders).
- Multi-Format Export: Supports generating reports in Markdown, PDF, or structured JSON for database integration.
SKILL.md
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