# Train Dot - [Root: Context Agent](https://docs.getdot.ai/train-dot/context-agent.md): Your AI data team member that builds and maintains your knowledge base - [Model](https://docs.getdot.ai/train-dot/model.md): Train Dot on your data model, semantic layer, documentation, ... - [Notes](https://docs.getdot.ai/train-dot/model/notes.md): Context is all you need - [Version Control](https://docs.getdot.ai/train-dot/version-control.md): Sync your context files with a Git provider for version control, audit trail, and AI/CI interoperability - [GitHub](https://docs.getdot.ai/train-dot/version-control/github.md): Sync your context files with GitHub for version control and automation interoperability - [GitLab](https://docs.getdot.ai/train-dot/version-control/gitlab.md): Sync your context files with GitLab for version control and AI/CI interoperability - [Permissions](https://docs.getdot.ai/train-dot/permissions.md): permissive or restrictive, however you like it - [User Feedback](https://docs.getdot.ai/train-dot/user-feedback.md): is valuable input for learning - [Workspaces](https://docs.getdot.ai/train-dot/workspaces.md): Separate environments for different teams - [Custom Skills](https://docs.getdot.ai/train-dot/custom-skills.md): Extend what Dot can do. --- # Agent Instructions: 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: ``` GET https://docs.getdot.ai/train-dot.md?ask= ``` The question should be specific, self-contained, and written in natural language. 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.