> For the complete documentation index, see [llms.txt](https://docs.marketcompass.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.marketcompass.ai/subnet/subnet-17.md).

# Subnet 17

Market Compass utilizes Commune AI, specifically Subnet 17, to gather real-time data from X (Twitter) at scale. Here's how the subnet operates:

1. **Query Creation:**
   * Queries are created to access the X (Twitter) API, targeting market-related topics.
2. **Query Distribution:**
   * Miners within Subnet 17 receive a unique query to perform every minute, just before each voting cycle begins.
3. **Query Validation:**
   * Miners return updates for all queries, ensuring that the data collected is fresh and relevant.
   * Trust is placed in miners by default, assuming they provide accurate and valid data.
4. **Backend Verification:**
   * An undisclosed endpoint in our backend verifies random queries with timestamps provided by miners.
   * If the response differs from the expected data, the miner is blacklisted, ensuring data integrity.
5. **New Miner Validation:**
   * New miners undergo validation checks upon their first request to ensure data accuracy and reliability.
6. **Scoring System:**
   * The scoring system rewards miners for providing valid data, with emission distributed evenly among valid miners.
   * This approach builds a resource base necessary for future development and expansion.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://docs.marketcompass.ai/subnet/subnet-17.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.