An AI-powered assistant for collecting, auditing, and formatting high-impact customer testimonials and social proof.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install afrexai-testimonial-collector
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install afrexai-testimonial-collector using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
Testimonial Collector is a specialized tool designed to help businesses bridge the gap between customer satisfaction and marketing leverage. It empowers teams to systematically request, refine, and organize social proof by generating personalized outreach and transforming raw feedback into compelling marketing assets.
By focusing on specific outcomes, numbers, and attribution, this entry in the Openclaw Skills library ensures that your testimonials are not just vague compliments but powerful conversion tools. It streamlines the process of extracting data-driven results from clients and ensures that every piece of social proof is formatted perfectly for website deployment, social media snippets, or detailed case studies.
To add this capability to your agent, use the following CLI command from the Openclaw Skills ecosystem:
clawhub install afrexai-testimonial-collector
Once installed, you can provide the skill with raw customer feedback or client names to begin the generation and formatting process.
The skill organizes testimonial data using a structured approach focused on credibility and impact:
| Attribute | Type | Description |
|---|---|---|
| Quote | String | The core 1-2 sentence high-impact statement |
| Attribution | Metadata | Includes Full Name, Job Title, and Company |
| Specific Result | Metric | Quantifiable outcomes like percentage of revenue growth or hours saved |
| Format Type | Category | Website block, Social snippet, or Case study format |
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