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

# Parallel Processing

> Process a list with a looped agent and aggregate the result.

```wire theme={"languages":{"custom":["/languages/wire.tmLanguage.json"]}}
input {
    tasks: [{ id: number, title: string, description: string }]
}

secrets {
    api_key: string
}

provider llm from openai {
    endpoint: "https://api.openai.com/v1"
    api_key: secrets.api_key
}

model fast from llm {
    id: "gpt-4.1-mini"
}

agent analyze_each for { id, title, description } in input.tasks {
    model: model.fast
    instruction: "Analyze task {{ id }}: {{ title }}. Details: {{ description }}."

    output {
        task_id: number
        summary: string
        risk: enum { low, medium, high }
    }
}

agent aggregate {
    model: model.fast
    instruction: "Aggregate these task analyses: {{ agent.analyze_each }}."

    output {
        overview: string
        high_risk_task_ids: [number]
    }
}

output {
    analyses: agent.analyze_each
    overview: agent.aggregate.overview
    high_risk_task_ids: agent.aggregate.high_risk_task_ids
}
```