Run it

The bash tool in this example runs model-written commands directly on your machine with no sandbox, and the fan-out runs several of those agents in parallel. Run it in a directory and environment you are comfortable exposing, and add sandboxing before adapting it for anything beyond local experimentation.

if __name__ == "__main__":
    task = (
        sys.argv[1]
        if len(sys.argv) > 1
        else "Explore the current directory, then give a thorough review: what it does, "
        "code-quality issues, and concrete improvements."
    )
    agent = ModeAgent(MODEL)
    print(agent.turn(task))
    agent.set_mode(False)
    print(agent.turn("Briefly summarize what you found above, no fan-out needed."))

const task =
  process.argv[2] ??
  "Explore the current directory, then give a thorough review: what it does, " +
    "code-quality issues, and concrete improvements.";
const agent = new ModeAgent(MODEL);
console.log(await agent.turn(task));
agent.setMode(false);
console.log(await agent.turn("Briefly summarize what you found above, no fan-out needed."));

var task = args.Length > 0
    ? args[0]
    : "Explore the current directory, then give a thorough review: what it does, "
        + "code-quality issues, and concrete improvements.";
Console.WriteLine(await Turn(task));
SetMode(false);
Console.WriteLine(await Turn("Briefly summarize what you found above, no fan-out needed."));

func main() {
	if err := run(context.Background()); err != nil {
		log.Fatal(err)
	}
}

func run(ctx context.Context) error {
	if docTestMode {
		defer os.RemoveAll(workDir)
	}
	task := "Explore the current directory, then give a thorough review: what it does, " +
		"code-quality issues, and concrete improvements."
	if len(os.Args) > 1 {
		task = os.Args[1]
	}
	agent := newModeAgent(modelID)
	answer, err := agent.turn(ctx, task)
	if err != nil {
		return err
	}
	fmt.Println(answer)

	agent.setMode(false)
	summary, err := agent.turn(ctx, "Briefly summarize what you found above, no fan-out needed.")
	if err != nil {
		return err
	}
	fmt.Println(summary)
	return nil
}

void main(String[] args) throws InterruptedException {
    String task = args.length > 0
            ? args[0]
            : "Explore the current directory, then give a thorough review: what it does, "
                    + "code-quality issues, and concrete improvements.";
    ModeAgent agent = new ModeAgent(MODEL);
    IO.println(agent.turn(task));
    agent.setMode(false);
    IO.println(agent.turn("Briefly summarize what you found above, no fan-out needed."));
}

$task = $argv[1] ??
    'Explore the current directory, then give a thorough review: what it does, '
    . 'code-quality issues, and concrete improvements.';
$agent = new ModeAgent($client, MODEL);
echo $agent->turn($task), PHP_EOL;
$agent->setMode(false);
echo $agent->turn('Briefly summarize what you found above, no fan-out needed.'), PHP_EOL;

task = ARGV[0] ||
  "Explore the current directory, then give a thorough review: what it does, " \
  "code-quality issues, and concrete improvements."
agent = ModeAgent.new(MODEL)
puts agent.turn(task)
agent.set_mode(false)
puts agent.turn("Briefly summarize what you found above, no fan-out needed.")

Start the example from the directory you want the agents to work in, for example the root of a repository to review:

python orchestration_mode.py "Review this repository for flaky tests and propose fixes."

With the mode on, expect the model to scout with a few bash commands, dispatch the Workflow tool unprompted, and synthesize the subagent reports into a final answer. Trivial or conversational requests stay solo, as the reminder instructs.