Best Practices

agent classify {
    model: model.fast
    instruction: "Classify {{ input.message }}."

    output {
        category: enum { bug, feature, question }
        confidence: number
    }
}

input {
    project_id: number
}

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"
}

mcp tasks {
    endpoint: "http://localhost:8000/mcp/tasks"
}

tool fetch_tasks from mcp.tasks.tool.fetch_tasks {
    input {
        project_id: number
    }

    output {
        tasks: [{
            id: number
            title: string
            description: string
            status: string
        }]
    }
}

dynamic {
    task_list: call tool.fetch_tasks {
        bindings {
            project_id: input.project_id
        }
    }
}

agent analyze_task for task in task_list.tasks {
    model: model.fast

    instruction: """
        Analyze this task and identify the next useful action.

        Task title: {{ task.title }}
        Task description: {{ task.description }}
        Task status: {{ task.status }}
    """

    output {
        task_id: number
        summary: string
        recommended_action: string
    }
}

agent summarize_project {
    model: model.fast

    instruction: """
        Create a project-level summary from these task analyses:

        {{ agent.analyze_task }}
    """

    output {
        summary: string
        next_actions: [string]
    }
}

output {
    task_analyses: agent.analyze_task
    project_summary: agent.summarize_project
}