> ## 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. # Task types > The task types an Automation can run — agent, execute_sql, formatter, and sub-automations Every task declares a `type` that selects the tool it runs. This page covers the core task types; iteration lives on the [Loops](/docs/guide/build/automations/loops) page. ## `type: agent` Runs an [agent](/docs/guide/build/agents) with a prompt. | Component | Description | Type | | ------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------- | | agent\_ref | The agent to use within the `agents` directory, referenced by the agent's `name`. | required for `type: agent` | | prompt | The input prompt passed to the agent for this task. | required for `type: agent` | | consistency\_run | Number of times to run the agent and select the most consistent output. Must be > 1 to enable. | optional (default: 1) | | consistency\_prompt | Custom evaluation prompt for consistency checking. Overrides Automation-level prompt. Supports Jinja templating with variables: `submission_1`, `submission_2`, `task_description`. | optional | ### Agent task consistency runs You can enable consistency checking on agent tasks by setting `consistency_run` to a value greater than 1. This runs the agent multiple times with the same prompt and selects the most consistent output: ```yaml theme={null} # Automation-level consistency prompt (applies to all agent tasks) consistency_prompt: | Your custom evaluation prompt here... Use {{ submission_1 }}, {{ submission_2 }}, and {{ task_description }} tasks: - name: calculate_revenue type: agent agent_ref: default prompt: "What was our total revenue last quarter?" consistency_run: 5 # Run 5 times and pick the most consistent result - name: analyze_trends type: agent agent_ref: default prompt: "What are the key sales trends?" consistency_run: 3 # Task-level prompt overrides Automation-level prompt consistency_prompt: | Compare these trend analyses focusing on directional consistency: Submission 1: {{ submission_1 }} Submission 2: {{ submission_2 }} Are they factually consistent? Answer A or B. ``` This is particularly useful for: * Critical calculations where consistency is important * Data analysis tasks that may have slight variations in output * Queries involving complex logic where you want to verify the agent's reasoning **Consistency prompt configuration:** * **Automation-level**: Add `consistency_prompt` at the root to apply to all agent tasks * **Task-level**: Add `consistency_prompt` to a specific task to override the Automation prompt * **Default**: If not specified, uses the built-in evaluation prompt optimized for data analysis (view the [default prompt source](https://github.com/oxy-hq/oxygen-internal/blob/main/crates/core/src/config/constants.rs#L52-L199)) **Available template variables:** * `{{ submission_1 }}` - First output * `{{ submission_2 }}` - Second output * `{{ task_description }}` - The task prompt **Note:** Custom prompts completely replace the default. To adapt the default for your domain, copy the [source](https://github.com/oxy-hq/oxygen-internal/blob/main/crates/core/src/config/constants.rs#L52-L199) and modify the specific rules you need. See the [Testing](/docs/guide/build/test-evaluate/testing#consistency-runs-in-workflow-agent-tasks) documentation for more details on consistency checking. ## `type: execute_sql` Executes a SQL query either referenced by filename or provided inline. | Component | Description | Type | | ---------- | ------------------------------------------------------- | ----------------------------- | | sql\_file | The sql file within the `data` directory to execute | required (or use `sql_query`) | | sql\_query | Inline SQL query to execute (alternative to `sql_file`) | required (or use `sql_file`) | | database | The name of the `database` to execute the query against | required | You can use either `sql_file` to reference a SQL file, or `sql_query` to provide the SQL inline. **Note:** These options are mutually exclusive—only one should be used at a time. Specifying both in a single task is not allowed. ```yaml theme={null} # Using sql_file - name: query_with_file type: execute_sql sql_file: my_query.sql database: local # Using sql_query inline - name: query_inline type: execute_sql sql_query: | SELECT * FROM users WHERE created_at > '2024-01-01' database: local ``` ## `type: formatter` Formats the provided `template` using the outputs of other `tasks`, then passes the rendered template as output. | Component | Description | Type | | --------- | ------------------------------------------------- | -------- | | template | The template to be rendered and passed as output. | required | ## `type: workflow` Runs another Automation as a sub-step. | Component | Description | Type | | --------- | -------------------------------------------------------------------------------------- | -------- | | src | Path to the Automation yml file to execute. Relative to the root of the oxy directory. | required | | variables | Variables that are passed through, overriding the sub-Automation's variables. | optional | Use this to break up complex Automations into smaller, easily testable chunks. The `variables` key allows parameterization by overriding the sub-Automation's Automation-level variables. This is particularly useful when embedding an Automation task into a loop: ```yaml theme={null} - name: loop_brands type: loop_sequential values: ["brand1", "brand2"] concurrency: 10 tasks: - name: brand_stats type: workflow src: brand_stats.automation.yml variables: brand_rollup: "{{ loop_brands.value }}" ``` ## Next steps Iterate over values with `loop_sequential` Parameterize tasks with typed inputs