> ## Documentation Index > Fetch the complete documentation index at: https://docs.soloent.ai/llms.txt > Use this file to discover all available pages before exploring further. # Subagents > Let the main Agent automatically dispatch read-only subagents to explore in parallel — saving context, speeding up loading, and controlling cost SoloEnt supports **collaboration between a main Agent and subagents**. Based on the task, the main Agent automatically dispatches subagents and assigns exploration work; multiple subagents run in **parallel** and then report their results back to the main Agent. This keeps the main Agent's context from being filled with large amounts of raw material during wide-ranging exploration. ## When it fits **Good for**: knowledge exploration, information gathering, and classification/collaboration — the main Agent assigns different exploration tasks to different subagents to complete in parallel, then aggregates the results. * Gathering weapon references, worldbuilding knowledge, and character design separately * Reading different chapters separately and then summarizing **Not good for**: * Assigning **repetitive** tasks to multiple subagents at once — different subagents repeatedly read the same context, which is wasteful * **Production/output** tasks — subagents focus on exploring, gathering, and organizing; they **have no write tools** and are not responsible for output ## Where to enable In **Agent Settings** you can turn subagents on or off. When enabled, the main Agent will automatically trigger subagent collaboration as the task requires. The subagent toggle in Agent feature settings, described as letting SoloEnt run read-only research subagents in parallel to gather evidence from your writing project For example, during wide-ranging knowledge exploration, the main Agent can delegate **read-only subagents** to run in parallel and aggregate the results back, greatly saving context. The main Agent running 3 subagents in parallel to analyze the previous 3 chapters, the characters, and the outline in support of writing the next chapter ## Configure a separate model for subagents Subagents mainly explore the information the main task needs, so you can pair them with a **different model from the main Agent**. Benefits of tuning this well: * Saves the main Agent's context * Parallel exploration speeds up information loading * Using a cheaper model lowers overall cost The SUBAGENT section in Agent Settings > API Configuration, where the subagent model can be set to Same as main or specified separately Learn how context is consumed and when to open a new window Turn reusable exploration/organization flows into Skills to use with subagents