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The Model Assistant is a chat panel in the Model IDE designed to help you build and maintain your semantic model. Use it to ask questions about your model, get suggestions for fields and relationships, and work through YAML edits.
The assistant is grounded in your current model and connection (topics, views, relationships, and field-level access controls), not arbitrary SQL against your warehouse. To improve answers across Omni AI, see Optimize models for Omni AI.

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Requirements

To use the Model Assistant, you need:

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Open the assistant

  1. Open a model in the Model IDE.
  2. In the IDE rail, click Show AI assistant (sparkles icon) to open the chat panel.
  3. Type in the prompt box. Your conversation stays in the panel while you switch files, save, or change modeling modes.

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Example prompts

You can ask in plain language. You do not need to paste YAML unless you want to point at something specific. 
How do the customers and orders views relate in this model?

Identify opportunities to improve AI context given this chat prompt: "How is my pipeline doing?"
- conflicting context
- redundant context
- missing context

Make sure to flag if any assumptions are being made so the user can make clarifications,

Update the model with your recommendations:
1. Write `ai_context` mapping business terms to fields
  - **Data nuances** — explain what isn't obvious from field names
2. Add `synonyms` to key dimensions and measures
  - Map alternative names, abbreviations, and domain-specific terminology so Blobby matches user queries to the correct field. Works on both dimensions and measures.
  - **Synonyms vs ai_context**: Use `synonyms` for field-level name mapping. Use `ai_context` for topic-level behavioral guidance, data nuances, and multi-field relationships.
3. Curate `ai_fields` to remove noise
  - Reduce noise for large models
4. Improve field `description` values
  - Good descriptions help both Blobby and human analysts.

Read the docs for skills and generate one based on the above prompt.

Create a dimension that groups the margin field in order_items into logical bins

Create a topic that groups our sales-related tables for self-serve reporting.

Fix the model validation errors

Update every revenue measure so they are all formatted with currency_2

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Built-in skills

The Model Assistant includes default skills that appear as clickable buttons below the prompt box. These skills guide the assistant through specialized tasks without requiring you to write detailed prompts.

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Optimize topic for AI

The Optimize topic for AI skill analyzes a topic and its views to identify opportunities for improving AI metadata. When you click this skill, the assistant asks which topic to analyze, then reviews metadata across four categories:
  • Token efficiency — Identifies verbose or redundant metadata and flags missing ai_fields directives that could reduce token usage
  • Clarity — Highlights ambiguous fields missing context and non-descriptive labels that may confuse the AI
  • Deduplication — Finds repeated information between ai_context and description fields, or between field-level and topic-level metadata
  • Sample queries — Reviews existing sample queries and recommends additions or improvements, including suggestions for golden datasets
After the analysis, the assistant provides specific recommendations and can apply changes directly to your model.
Use this skill regularly when building or updating topics to ensure your AI metadata supports high-quality query generation and reduces unnecessary token consumption. For guidance on AI optimization beyond this skill, see Optimize models for Omni AI.

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Modeling modes

The panel includes a mode menu so you control how proposed model changes are applied. Your selected mode persists between sessions.
ModeHow it worksBest for
SandboxProposes all changes at once. You review and accept or reject before anything is written.Exploring ideas, pressure-testing updates, and reviewing larger changes before they enter the model.
ReviewWrites changes, then pauses for your approval before continuing.Step-by-step collaboration when you want close oversight as changes are made.
AutoApplies changes immediately, including branch creation, without pausing.Fast iteration when you’re already working on a branch.
In Sandbox mode, all proposed changes are bundled and presented as expandable diffs for each affected file. You make a single Accept all or Reject all decision before anything is written to the model.
If you edit the shared model, your workflow may require a branch before the assistant can write changes. Create a branch from the IDE when prompted, then continue the conversation.

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Next steps

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Troubleshooting

I don’t see the sparkles / Show AI assistant control. Confirm Query assistant is on in Settings > AI and that your role can access the Model IDE for the connection. The assistant won’t apply edits. On the shared model you may need a branch first. Create a branch in the IDE, then ask again. Answers feel generic. Add richer descriptions, AI context on views and topics, and sample queries so Omni’s AI has more to work with across the product.

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Getting help

If you’re stuck and can’t remember how to do something in Omni, just ask Blobby. Questions like “How do I do [thing]?” will prompt Blobby to search the official Omni docs and provide you with an answer, all without leaving your Omni workflow. You can also directly tell Blobby to search the docs when researching the answer to your question.
Working in an embedded context? If you have the Hide Omni watermark setting enabled to provide a fully white-labeled experience, the AI doc search feature will respect it. Omni doc links will not be returned in chat, even if explicitly requested.