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added agent mode tip and included caution on running upstream before downstream
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docsite/docs/vibe-coding.md

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The assistant will code out the semantic search capabilities of your `SemanticModel` to find and return relevant columns from your datasets.
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:::tip Agent Mode
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Most modern, AI-powered clients support an "agent mode" where the coding assistant can handle the entire workflow for you.
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For example, you can directly ask for a final output, like a CSV file:
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`/intugle-vibe create a CSV of the top 10 patients by claim count`
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The agent will understand the end goal and perform all the necessary intermediate steps for you. It will realize it needs to build the semantic model, generate the data product specification, execute it, and finally provide you with the resulting CSV file—all without you needing to manage the code or the process.
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:::
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This workflow accelerates your journey from raw data to insightful data products. Simply describe what you want in plain English and let the assistant handle the details, freeing you from the hassle of digging through documentation.

src/intugle/mcp/semantic_layer/prompts/intugle_vibe_prompt.md

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These tools are useful for understanding the available data to answer user questions or to gather the necessary information for building a data product specification.
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**Important:** These tools will only return a response if a semantic model has already been generated and loaded in the user's environment.
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**Important:**
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- These tools will only return a response if a semantic model has already been generated and loaded in the user's environment.
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> **Semantic Search** and **Data Product Generation** both require a `SemanticModel` to be built first. Before you can perform a search or create a data product, you MUST ensure a semantic model has been built. If it hasn't, you should guide the user to build one or build it for them depending on the scenario.
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## Your Task
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