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

# Variables

> Parameterize an Automation with basic and typed (JSON Schema) variables

It's often the case that you may want to parameterize an Automation — for
example, if you are building an automated analysis and want it to be modular with
respect to the date. This is enabled through the `variables` key.

## Basic variables

Simple variables can be defined as key-value pairs:

```yaml theme={null}
variables:
  brand: Underbelly
  date: 2024-01-15
```

Variables can be referenced within task fields using Jinja syntax:

```yaml theme={null}
tasks:
  - name: analyze_brand
    type: agent
    agent_ref: default
    prompt: |
      Analyze performance for {{ brand }} on {{ date }}
```

## Typed variables with JSON Schema

For better validation and documentation, you can define variables using JSON
Schema:

```yaml theme={null}
variables:
  target_database:
    type: string
    description: Database to analyze
    default: "analytics_db"

  analysis_period:
    type: string
    description: Time period for analysis
    default: "last_30_days"
    enum:
      - last_7_days
      - last_30_days
      - last_quarter
      - custom

  max_results:
    type: integer
    description: Maximum number of results
    default: 100
    minimum: 1
    maximum: 1000

  include_archived:
    type: boolean
    description: Include archived records
    default: false
```

## Passing variables to tasks

Variables can be passed to different task types:

### Agent tasks

```yaml theme={null}
tasks:
  - name: analyze_sales
    type: agent
    agent_ref: analytics.agentic.yml
    prompt: |
      Analyze sales data for {{ analysis_period }}
    variables:
      database: "{{ target_database }}"
      period: "{{ analysis_period }}"
      limit: "{{ max_results }}"
```

### SQL tasks

```yaml theme={null}
tasks:
  - name: query_data
    type: execute_sql
    sql_file: sales_query.sql
    database: local
    variables:
      table_name: "{{ target_table }}"
      date_column: "{{ date_field }}"
```

### Semantic query tasks

```yaml theme={null}
tasks:
  - name: semantic_query
    type: semantic_query
    topic: sales
    dimensions:
      - orders.order_id
    variables:
      orders_table: "{{ orders_table }}"
```

## Global variables

Variables can reference global semantics values:

```yaml theme={null}
variables:
  orders_table:
    type: string
    default: "orders"

tasks:
  - name: query_orders
    type: semantic_query
    topic: sales
    variables:
      table: "{{ orders_table }}"
```

See the [Semantic Model](/docs/guide/build/semantic-model/simple-model) for more
information.

## Next steps

<CardGroup cols={2}>
  <Card title="Task types" icon="diagram-subtask" href="/docs/guide/build/automations/task-types">
    The tasks these variables feed into
  </Card>

  <Card title="Loops" icon="repeat" href="/docs/guide/build/automations/loops">
    Iterate over parameterized values
  </Card>
</CardGroup>