# Sheet Search

Sheet search tools let agents search through spreadsheet data you've uploaded to your knowledge base. This is useful for structured data that doesn't fit well in documents.

**Plan required:** All plans

## Use Cases

* Product specifications and catalogs
* Pricing tables
* Store location data
* FAQ databases in tabular format
* Inventory information
* Employee directories

## How It Works

When you add a spreadsheet to your knowledge base, it can be enabled as a searchable tool. The agent can then query this data to answer user questions with up-to-date information from your spreadsheets.

## Step 1: Add Your Sheet

<figure><img src="/files/4Ocl6gSzsxw9rX1ruZEz" alt=""><figcaption></figcaption></figure>

1. Navigate to **AI Settings** and go to the **Train your AI agent** tab
2. Locate the **Add sources to your knowledge base** section
3. Paste a Google Sheets link into the input field or upload a sheet file
4. Click **Add Link** to add the sheet to your knowledge base

## Step 2: Configure Your Sheet

<figure><img src="/files/wRNYVqmY2DXyBZ06iAVY" alt=""><figcaption></figcaption></figure>

After the sheet is added, a "Sheet detected" modal will appear. You have two options:

* **Configure sheet settings** - Fine-tune which columns are indexed and prioritized for search results. Recommended for optimal AI performance.
* **Skip for now** - Start using the sheet with default settings. You can configure it later from the Actions menu.

## Step 3: Sheet Settings

<figure><img src="/files/n4SfrWTVnocNa8jHT6IH" alt=""><figcaption></figcaption></figure>

After clicking **Configure sheet settings**, you'll see the configuration page.

### Enable Sheet Search Integration

Toggle **Enable sheet search integration** to activate this feature. When enabled, the agent will query this sheet when answering user questions.

### Edit Sheet Details

| Field           | Description                                                            |
| --------------- | ---------------------------------------------------------------------- |
| **Sheet name**  | Display name for your sheet                                            |
| **Description** | What data this sheet contains (helps the agent know when to search it) |

{% hint style="info" %}
Write specific descriptions. Instead of "Product data", write "Product catalog with 500+ items including SKUs, prices, dimensions, and availability status."
{% endhint %}

### Configure Column Indexing

Select which columns should be ingested and prioritized in the knowledge base.

Columns marked with **priority** will be weighted more heavily when the AI searches for relevant information.

### Save Your Configuration

Click **Save changes** to apply the configuration. Your sheet is now ready to be searched by the agent.

## Adjusting Settings Later

<figure><img src="/files/e3RdI71QwwhZqSETmndm" alt=""><figcaption></figcaption></figure>

To access configuration after initial setup:

1. Find the sheet entry in your knowledge base sources list
2. Click the **Actions** dropdown menu
3. Select **Configure sheet settings**

## Assigning to Agents

Once configured, enable the sheet search tool for specific agents:

1. Navigate to **AI Settings > Agents**
2. Select the agent you want to configure
3. In the Tools section, enable the sheet search tool
4. Save your changes

## Best Practices

### Keep data clean

Ensure your spreadsheet has clear headers and consistent formatting. See [spreadsheet formatting best practices](https://github.com/Gleen-AI/gitbook-docs/blob/main/integrations/data-sources/csv-excel-and-google-sheets-ingestion.md#best-practices-checklist-quick).

### Use meaningful descriptions

Be specific about what data the sheet contains and when the agent should search it.

### Prioritize key columns

Mark columns most relevant to user queries as priority. This helps the agent find the right information faster.

### Keep data current

Regularly update your sheet data so the AI always has access to the latest information.

### Test with sample queries

After configuring a sheet, test the AI with sample queries to ensure it retrieves the expected data.

## Supported Formats

* Google Sheets (via link)
* CSV files
* Excel files (.xlsx, .xls)

For detailed information on preparing spreadsheet files, see [CSV, Excel & Sheets](https://github.com/Gleen-AI/gitbook-docs/blob/main/integrations/data-sources/csv-excel-and-google-sheets-ingestion.md).

## Troubleshooting

| Issue                          | Solution                                             |
| ------------------------------ | ---------------------------------------------------- |
| Agent doesn't search the sheet | Verify the sheet is enabled as a tool for that agent |
| Wrong data returned            | Check column priorities and sheet description        |
| Data is outdated               | Re-sync the sheet from the knowledge base            |
| Search is slow                 | Reduce the number of indexed columns to essentials   |

## Related

* [API Tools](/docs/integrations/custom-extensions/api-tools.md) - For HTTP API integrations
* [MCP Servers](/docs/integrations/custom-extensions/mcp-servers.md) - For complex integrations
* [CSV, Excel & Sheets](/docs/ai-configuration/data-sources/csv-excel-and-google-sheets-ingestion.md) - Data source setup


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# 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://alhena.gitbook.io/docs/integrations/custom-extensions/sheet-search.md?ask=<question>
```

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.