> For the complete documentation index, see [llms.txt](https://docs.maiagent.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.maiagent.ai/maiagent-user-guide/en/built-in-agents.md). # Agent Marketplace - [What Are Official Built-in Agents?](https://docs.maiagent.ai/maiagent-user-guide/en/built-in-agents/built-in-agents.md): Official built-in Agents are AI assistants created by MaiAgent and listed in the Agent Marketplace. Once enabled by an organization, they are ready to use with no setup required. - [Use Official Built-in Agents](https://docs.maiagent.ai/maiagent-user-guide/en/built-in-agents/use.md): Choose an official built-in Agent from the Agent Marketplace, upload source material, clarify requirements, and receive downloadable output. - [Enable and Manage](https://docs.maiagent.ai/maiagent-user-guide/en/built-in-agents/management.md): Learn how organization administrators enable official built-in Agents, configure authorized users and knowledge bases, and manage enablement limits, cooldown periods, and deactivation. --- # 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.maiagent.ai/maiagent-user-guide/en/built-in-agents.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. 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.