# ai_generate_scoring_model (/docs/mcp/tools/ai-generate-scoring-model)

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**AI-generate a scoring model** · Changes data

Have AI build a lead scoring model from the website's own pages (it reads the site to infer the ideal customer) and save it as 'ICP Score - AI Generated'. Only one such model can exist per website; a second call is refused with 'AI Lead scoring model has already been generated!'. Pass description to steer it: the ideal customer as the user describes it takes priority over what the site suggests. For exact rules use create_lead_scoring_model instead. websiteId comes from list_websites. Returns result (the new model with _id and its rules).

| Connection | Account URL, team member URL or OAuth |
| --- | --- |

## Parameters [#parameters]

| Parameter | Type | Required | Description |
| --- | --- | --- | --- |
| `websiteId` | `string` | Yes | Website id (24 hex characters) from list_websites. |
| `description` | `string` | Yes | Plain-English description of the ideal customer, e.g. "US software companies with 50-500 staff selling to finance teams". Steers the generated rules. |

## Tool definition [#tool-definition]

What your assistant receives from `tools/list`:

```json
{
  "name": "ai_generate_scoring_model",
  "title": "AI-generate a scoring model",
  "annotations": {
    "title": "AI-generate a scoring model",
    "readOnlyHint": false,
    "destructiveHint": false,
    "idempotentHint": true,
    "openWorldHint": false
  },
  "inputSchema": {
    "type": "object",
    "properties": {
      "websiteId": {
        "type": "string",
        "description": "Website id (24 hex characters) from list_websites."
      },
      "description": {
        "type": "string",
        "description": "Plain-English description of the ideal customer, e.g. \"US software companies with 50-500 staff selling to finance teams\". Steers the generated rules."
      }
    },
    "required": [
      "websiteId",
      "description"
    ]
  }
}
```