> For the complete documentation index, see [llms.txt](https://omniminds-ai.gitbook.io/whitepaper/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://omniminds-ai.gitbook.io/whitepaper/4.-who-are-we/crowdsourced-agent-ecosystem.md).
# Crowdsourced Agent Ecosystem
Omniminds enables an open ecosystem of contributors who can create, improve, and validate agents. Each contributor who trains AI agents is compensated with the $OMNI tokens. An AI generates a score for your demonstration quality, which determines how much you’d be incentivized. Every participant has a role:
* Users train agents by demonstrating tasks
* Developers build composable logic modules and fine-tune behaviors
* Validators test and audit agent performance
* Curators organize, optimize, and manage agent libraries
* Communities govern the evolution of agent behaviors
This crowdsourced structure ensures the scalability, diversity, and adaptability of AI behaviors while allowing everyone to earn rewards for their contributions.
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# 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://omniminds-ai.gitbook.io/whitepaper/4.-who-are-we/crowdsourced-agent-ecosystem.md?ask=&goal=
```
`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.
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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.