# Running Sub-Workflows to Iterate and Process Data

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Using sub-workflows in MindStudio enables you to break out a specific task (like scraping a URL or generating summaries) and apply it repeatedly across a list of items. This approach is highly effective when dealing with variable-length structured data such as JSON arrays.

### Why Use Sub-Workflows?

When dealing with dynamic lists (like search results or multiple URLs), manually duplicating logic is inefficient and error-prone. Instead, sub-workflows allow you to:

* Reuse logic
* Keep workflows modular and organized
* Handle variable-length lists
* Execute iterations in parallel or sequentially

### Parent Workflow Overview

The parent workflow in this example:

1. Accepts a topic as input
2. Runs a **Google Search** block
3. Iterates over the returned list of URLs
4. For each URL, runs a sub-workflow to scrape and summarize content
5. Aggregates the results and uses them to generate a long-form article

### Creating the Sub-Workflow

The sub-workflow (`scrape URL`) should:

* Accept a **launch variable**: `URL`
* Use a **Scrape URL** block to get page content
* Generate a **summary**, **key takeaways**, and **quotes**
* Return a structured JSON object with these outputs

Example JSON output from the sub-workflow:

```json
{
  "url": "...",
  "summary": "...",
  "takeaways": ["..."],
  "quotes": ["..."]
}
```

### Setting Up the Run Workflow Block

In the parent workflow:

1. **Add a Run Workflow block**
2. Select the sub-workflow you created
3. Switch mode to **Run Multiple Times**
4. Under **Input Data**, pass the output from the Google Search block (e.g., `search`)
5. Use **Auto Extract** or **JSON Array Input**:

#### Option 1: Auto Extract

* Use a prompt like `extract all URLs`
* Reference the extracted value as `item`

#### Option 2: JSON Array Input (Recommended for Structured Data)

* Choose `JSON Array Input`
* Use dot notation to reference: `item.url`

6. Configure **Execution Mode**:
   * **Parallel**: Recommended for speed if iterations are independent
   * **Sequential**: Use when order matters or there's shared state
7. Set **Error Behavior**:
   * Choose whether to fail on errors or ignore failed runs
   * Set retry attempts if needed
8. Define **Output Variable**:
   * For example: `sources` (an array of all scraped summaries)

### Using Sub-Workflow Output

Once all sub-workflows complete:

* The output (`sources`) can be passed into a **Generate Text** or **Generate Asset** block
* You can format this data into:
  * An HTML page
  * A long-form article with footnotes
  * A structured JSON document

### Example Use Case

* Input topic: `"Future of Space Travel"`
* Google Search returns \~27 results
* Each URL is processed in the `scrape URL` sub-workflow
* Resulting summaries are aggregated and used to generate a detailed article with citations and source list

### Benefits of Sub-Workflow Design

* **Scalable**: Works with any number of inputs
* **Modular**: Easier to maintain or reuse scrape logic
* **Flexible**: You can switch sources, change formats, or reuse logic across different agents

### Summary

Running sub-workflows in MindStudio allows you to:

* Iterate over dynamic lists
* Process and transform structured data
* Improve workflow performance using parallel execution
* Simplify complex builds with modular design

Use sub-workflows whenever you need to apply the same logic repeatedly to parts of a list—especially when dealing with external data, scraping, or transforming structured JSON.


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