> ## Documentation Index
> Fetch the complete documentation index at: https://deepline.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Datagma: Enrich Person

> Enrich a person from a LinkedIn URL, email, or name plus company with email, mobile phone, job title, company, and location.

Enrich a person from a LinkedIn URL, email, or name plus company with email, mobile phone, job title, company, and location.

> [!NOTE]
>
> Tool ID: `datagma_enrich_person`

## Run this action

Use the TypeScript SDK for one call. Use `ctx.tools.execute(...)` inside a Play for durable calls, scheduled calls, or CSV processing.

```ts theme={"languages":{"custom":["/languages/deepline-prompt.json"]}}
import { Deepline } from 'deepline';

const deepline = await Deepline.connect();
const result = await deepline.tools.execute(
  'datagma_enrich_person',
  {
    "linkedin": "https://www.linkedin.com/in/jane-doe",
    "email": "jane.doe@example.com",
    "fullName": "Example"
  },
);

console.log(result.toolResponse.raw);
```

### CLI

```bash theme={"languages":{"custom":["/languages/deepline-prompt.json"]}}
deepline tools execute datagma_enrich_person --input '{
  "linkedin": "https://www.linkedin.com/in/jane-doe",
  "email": "jane.doe@example.com",
  "fullName": "Example"
}' --json
```

## Example response

The SDK returns this shape at `result.toolResponse.raw`. The example values illustrate the response.

```json theme={"languages":{"custom":["/languages/deepline-prompt.json"]}}
{
  "id": "id_123",
  "full_name": "Example",
  "first_name": "Jane"
}
```

Use `deepline describe datagma_enrich_person --json` for the latest machine-readable contract.

## Input reference

Compatibility person enrichment input that preserves the legacy Datagma public contract while routing through shared V2 enrichment.

| Name | Type | Required | Default | Details |
| - | - | - | - | - |
| `payload.linkedin` | `string` | No | — | — |
| `payload.email` | `string` | No | — | — |
| `payload.fullName` | `string` | No | — | Minimum length: 1. |
| `payload.companyName` | `string` | No | — | Minimum length: 1. |
| `payload.domain` | `string` | No | — | Minimum length: 1. |
| `payload.phone` | `string` | No | — | Minimum length: 1. |
| `payload.phoneFull` | `boolean` | No | — | Opt in to mobile phone lookup during enrichment. Omitted or false preserves basic enrichment. Mobile lookup costs more. inspect the payload estimate before running a batch. |

<details>
  <summary>Show raw input schema</summary>

  ### Input JSON Schema

  ```json theme={"languages":{"custom":["/languages/deepline-prompt.json"]}}
  {
    "type": "object",
    "description": "Compatibility person enrichment input that preserves the legacy Datagma public contract while routing through shared V2 enrichment.",
    "properties": {
      "linkedin": {
        "type": "string"
      },
      "email": {
        "type": "string"
      },
      "fullName": {
        "type": "string",
        "minLength": 1
      },
      "companyName": {
        "type": "string",
        "minLength": 1
      },
      "domain": {
        "type": "string",
        "minLength": 1
      },
      "phone": {
        "type": "string",
        "minLength": 1
      },
      "phoneFull": {
        "type": "boolean",
        "description": "Opt in to mobile phone lookup during enrichment. Omitted or false preserves basic enrichment. Mobile lookup costs more; inspect the payload estimate before running a batch."
      }
    },
    "additionalProperties": false
  }
  ```
</details>

## Output reference

| Name | Type | Required | Default | Details |
| - | - | - | - | - |
| `result.id` | `string` | No | — | — |
| `result.full_name` | `string` | No | — | — |
| `result.first_name` | `string` | No | — | — |
| `result.last_name` | `string` | No | — | — |
| `result.email` | `string` | No | — | — |
| `result.professional_email` | `string` | No | — | — |
| `result.personal_email` | `string` | No | — | — |
| `result.phone` | `string` | No | — | — |
| `result.mobile_phone` | `string` | No | — | — |
| `result.linkedin` | `string` | No | — | — |
| `result.title` | `string` | No | — | — |
| `result.seniority` | `string` | No | — | — |
| `result.department` | `string` | No | — | — |
| `result.location` | `object` | No | — | — |
| `result.location.city` | `string` | No | — | — |
| `result.location.state` | `string` | No | — | — |
| `result.location.country` | `string` | No | — | — |
| `result.location.country_code` | `string` | No | — | — |
| `result.company` | `object` | No | — | Native Datagma full-enrichment response. Deepline does not flatten this payload. Use the declared company\_name and domain getters for canonical values. |
| `result.company.company` | `object` | No | — | — |
| `result.company.company.basic` | `record` | No | — | — |
| `result.company.company.premium` | `record` | No | — | — |
| `result.experience` | `array` | No | — | — |
| `result.education` | `array` | No | — | — |
| `result.skills` | `array` | No | — | — |
| `result.languages` | `array` | No | — | — |
| `result.twitter` | `string` | No | — | — |
| `result.github` | `string` | No | — | — |
| `result.summary` | `string` | No | — | — |
| `result.followers` | `number` | No | — | — |
| `result.connections` | `number` | No | — | — |
| `result.is_decision_maker` | `boolean` | No | — | — |
| `result.job_change_detected` | `boolean` | No | — | — |
| `result.last_updated` | `string` | No | — | — |
| `result.confidence_score` | `number` | No | — | — |
| `result.data_sources` | `array` | No | — | — |

<details>
  <summary>Show raw output schema</summary>

  ### Output JSON Schema

  ```json theme={"languages":{"custom":["/languages/deepline-prompt.json"]}}
  {
    "type": "object",
    "properties": {
      "id": {
        "type": "string"
      },
      "full_name": {
        "type": "string"
      },
      "first_name": {
        "type": "string"
      },
      "last_name": {
        "type": "string"
      },
      "email": {
        "type": "string"
      },
      "professional_email": {
        "type": "string"
      },
      "personal_email": {
        "type": "string"
      },
      "phone": {
        "type": "string"
      },
      "mobile_phone": {
        "type": "string"
      },
      "linkedin": {
        "type": "string"
      },
      "title": {
        "type": "string"
      },
      "seniority": {
        "type": "string"
      },
      "department": {
        "type": "string"
      },
      "location": {
        "type": "object",
        "properties": {
          "city": {
            "type": "string"
          },
          "state": {
            "type": "string"
          },
          "country": {
            "type": "string"
          },
          "country_code": {
            "type": "string"
          }
        },
        "additionalProperties": true
      },
      "company": {
        "type": "object",
        "description": "Native Datagma full-enrichment response. Deepline does not flatten this payload; use the declared company_name and domain getters for canonical values.",
        "properties": {
          "company": {
            "type": "object",
            "properties": {
              "basic": {
                "type": "object",
                "additionalProperties": true
              },
              "premium": {
                "type": "object",
                "additionalProperties": true
              }
            },
            "additionalProperties": true
          }
        },
        "additionalProperties": true
      },
      "experience": {
        "type": "array",
        "items": {
          "type": "object",
          "additionalProperties": true
        }
      },
      "education": {
        "type": "array",
        "items": {
          "type": "object",
          "additionalProperties": true
        }
      },
      "skills": {
        "type": "array",
        "items": {
          "type": "string"
        }
      },
      "languages": {
        "type": "array",
        "items": {
          "type": "string"
        }
      },
      "twitter": {
        "type": "string"
      },
      "github": {
        "type": "string"
      },
      "summary": {
        "type": "string"
      },
      "followers": {
        "type": "number"
      },
      "connections": {
        "type": "number"
      },
      "is_decision_maker": {
        "type": "boolean"
      },
      "job_change_detected": {
        "type": "boolean"
      },
      "last_updated": {
        "type": "string"
      },
      "confidence_score": {
        "type": "number"
      },
      "data_sources": {
        "type": "array",
        "items": {
          "type": "string"
        }
      }
    },
    "additionalProperties": true
  }
  ```
</details>

## Deepline cost

* Pricing model: `provider_usage` (provider usage).
* Estimated Deepline credits: `0.27` per pricing unit.

## Related documentation

* [Datagma provider guide](https://deepline.com/docs/providers/datagma/guide.md)
* [SDK V2 quickstart](https://deepline.com/docs/sdk-v2/quickstart.md)
* [SDK reference](https://deepline.com/docs/sdk-v2/sdk-reference.md)
* [Run tools across a CSV](https://deepline.com/docs/sdk-v2/batch-csv.md)


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