.dinoprompts

The .dinoprompts file serves as your team's prompt library, allowing you to store and reuse battle-tested prompts that understand your data development patterns. This eliminates the need to recreate complex prompts and ensures consistency across your analytics engineering team.

Key Benefits

• Centralized Library: Store tailored prompts for analytics engineering workflows

• Time Savings: Access proven prompts instantly instead of recreating them

• Team Knowledge Sharing: Distribute effective prompts across your organization

• Context-Aware: Use variables for dynamic, situation-specific prompts

• Fast Onboarding: New team members access best practices immediately

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Step-by-Step Instructions

1. Open DinoAI by clicking the DinoAI icon (🪄) in the left panel

2. Access Prompt Creation by clicking the Prompt option in the chat input

   1. Alternative: Use the bracket symbol shortcut "[" to quickly find prompts

3. Create the file by selecting "Add .dinoprompts" to automatically create a new file with built-in prompts

4. Define your prompts using the YAML structure with name and prompt fields

5. Access your prompts using the prompt quick-open feature in DinoAI

Make sure the .dinoprompts file is placed in the root directory of your repository

your-repository
├── dbt_project/
│   ├── staging/
│   └── marts/
├── macros/
├── seeds/
├── .dinoprompts              # .dinopropmts file location
├── README.md

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File Structure

The .dinoprompts file uses a simple YAML structure:

prompts:
  - name: "Prompt Name"
    prompt: |
      Multi-line prompt content
      Can include variables like {{ git.diff.withOriginDefaultBranch }}
      
  - name: "Another Prompt"
    prompt: "Single line prompts work too"

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Available Variables

DinoAI provides built-in variables you can use in your prompts. Variables enable you to dynamically attach context to your prompts.

Vairable	Descriription
{{ git.diff.withOriginDefaultBranch }}	Includes the git diff between your current branch and the default branch of your repository
{{ editor.currentFile.path }}	Includes the file path of the current opened and selected file in your Code IDE
{{ editor.openFiles.path }}	Includes the file path of the all the opened files in your Code IDE

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Best Practices

1. Be Specific: Include clear requirements and expected outputs

2. Use Variables: Leverage context-aware substitutions

3. Provide Examples: Include sample inputs/outputs when helpful

4. Iterate: Test and refine prompts based on results

5. Descriptive Names: Use clear, purpose-driven prompt names

6. Team Collaboration: Share and improve prompts regularly

Common Use Cases

Ready-made prompts for analytics engineering tasks:

• Model Generation: Staging, intermediate, and mart models with proper structure

• Code Review: Git diff analysis for best practices and performance

• Documentation: Comprehensive model and column descriptions

• Testing: Data quality tests for models and transformations

• Optimization: Query performance improvements and bottleneck identification

• Standards: Consistent formatting and naming convention enforcement