This document serves as a guideline for framing scenarios involving interactions with Verax and a large language model from a user perspective. It aims to provide a simple understanding for the discoverability of Verax, interaction with algorithms, and understanding the approaches to ownership, privacy, and collaboration.

Describe Verax to a Large Language Model from the User Perspective:

How does the user interact with the large language model? What types of queries can the user submit? How does the model process and respond to these queries?

What is Verax's approach to information discovery?

What's the role of information discovery for Verax?

Example user queries in natural language:

Tell me about [Topic/Subject]?

How do I [Task/Action] in [Language/Tool]?

Example user actions in natural language:

Create [Output] based on [Input].

Capabilities of Verax in composability with other contextual entities

Do you think Verax shines when used in a composable way with other contextual entities or protocols? (hint: intent, reputation, trust, identity, knowledge, and maybe something else.)

Example, feel free to customize:

Adding to [knowledge:Apollo’s note], I have found a [context:new update] from [identity:Joel of Ceramic Network]. Verax mentioned is now being used by the first decentralized semantic index, demonstrating the potential use cases of Ceramic for AI and information discovery. I will be monitoring the project's progress, as you are [claim:curious] about Ceramic.

What is Verax's approach to collaboration?

How does Verax facilitate collaborative efforts between users or between users and AI agents?

What is Verax’s approach to privacy?

Describe Verax' privacy structure, especially from the information discovery perspective.

What are the data models, and where are they?