Toolbar Controls
Attach Context
Click the @ icon to attach context to your prompt, such as files or folders from your project. This helps DinoAI understand the specific parts of your codebase you are referring to, leading to more accurate and relevant responses.
DinoAI Settings
Click the Settings icon to open the DinoAI Settings panel, where you can manage tool permissions and connected integrations for your DinoAI agent.
Chat History
Click the Clock icon to open your DinoAI Chat History, where you can browse and reopen previous conversations with the agent.
God Mode
Click the Lock icon to toggle God Mode. When enabled, DinoAI will execute all actions autonomously without pausing to ask for your review or approval.
Mode Selection
The ∞ Agent dropdown lets you switch between two modes of interaction:
Model Selection
The model dropdown (displayed as Sonnet 4.6 by default) allows you to choose which underlying AI model powers your DinoAI session. Different models may vary in speed, capability, and suitability for different types of tasks.
Suggested Actions
Below the prompt bar, DinoAI surfaces a set of Suggested Actions — one-click prompts that are dynamically generated based on the files you currently have open in the Editor.
- Explain this model — get a plain language explanation of the dbt™ model currently open
- Document my dbt™ model — automatically generate documentation for your model
- Refactor dbt™ model — get recommendations or apply refactoring to your dbt™ model
- Debug failing dbt™ model — diagnose and fix issues with a failing dbt™ model
- Write unit tests — generate unit tests for the model in focus
- Create .dinoprompts — create a
.dinopromptsfile to save and reuse custom prompts in your project
Suggested actions are context-aware. For the most relevant suggestions, make sure the file you want to work on is active and open in the Editor.
Related
- .dinorules — Set rules that apply to all Copilot interactions
- .dinoprompts — Save and reuse prompts across your team
- DinoAI Settings — Configure Copilot behaviour and model preferences