LLM

The LLM node sends a prompt to a language model and produces its response for the next node to use. You pick the model, write the prompt and system instructions, and optionally connect tools the model can call. It has two modes: Agent, a normal step that always runs as part of the flow, and Sub-agent, a helper that doesn’t run on its own but is exposed to a main agent as a callable tool.

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Modes

Set the mode with the Used as dropdown at the top of the node. Everything else, including model, prompt, and tools, is configured the same way in both modes. Only how the node participates in the flow changes. For the full picture of how agents call tools and sub-agents, see Agents and tools.

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Inputs

Input handles are on the left of the node.

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Outputs

Output handles are on the right of the node.

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Settings

• Used as — the mode dropdown: Agent or Sub-agent.
• Model — the language model that runs. Filtered to models that produce text output.
• Prompt — the instruction the model acts on. Type {{topic}} or another variable token to expose a dedicated input handle for that part of the prompt. In Sub-agent mode the prompt is reserved for the main agent and isn’t editable on the node.
• System instructions — the model’s standing behavior, separate from the per-run prompt.
• Structured output — optional output fields that make the model return a structured object instead of free text.
• Tools — connect Tool nodes and Sub-agents via the tools input to give the model abilities it can call.
• Advanced Settings — extra model parameters (such as temperature) under a collapsible section. The available parameters depend on the selected model.

In Sub-agent mode, two more settings appear:

• Tool name — a short identifier the parent agent uses to call this sub-agent (for example research_assistant). Spaces and invalid characters are cleaned up automatically.
• Tool description — tells the parent agent when to call this sub-agent. Be specific about the task it handles; the main agent reads this to decide whether to invoke it.

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Structured output

Structured output lets an Agent produce named fields instead of one free-text response. Add fields in the structured output builder, give each field a name, and connect downstream nodes to the field handles you need. Each field can use one of six shapes: Fields can be mixed freely, including multiple list fields. The overall schema shape determines whether the node fans out: For example, title plus description exposes two handles on one item. A sole ideas[] field containing five values emits five items. A title plus tags[] schema emits one item, with tags serialized as JSON text on its handle. Field names must start with a letter or underscore and contain only letters, numbers, and underscores. Names ending in _<number> are reserved for item ordinals. Enum fields need at least one option. Number ranges and minimum list lengths guide the model. A list’s maximum item count is also enforced as a hard output cap and contributes to the pre-run count and cost estimate. Structured output runs as object generation. Tool calling is skipped for that run shape, so use normal Agent mode without a schema when the model should actively call tools while composing the answer.

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Sub-agent mode

A sub-agent does not run as part of the main flow. Instead, a main Agent reads its tool name and tool description and decides, mid-run, whether the current task needs it. This lets you split a big problem into focused roles, such as researcher, writer, or validator, that the main agent orchestrates. To use one: Constraints to keep in mind:

• Max sub-agent depth is 5. Sub-agents can call sub-agents, but the call chain can’t nest deeper than five levels.
• Tool names must be unique per parent agent. Two sub-agents wired into the same Agent can’t share a tool name.
• No sub-agent cycles. A sub-agent can’t call back into a chain that leads to itself.

See Agents and tools for the full model, and the Tool node for wiring built-in tools.

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When to use

• Agent — for any step that should always run: drafting text, summarizing, classifying, transforming an upstream result, or driving tools toward a fixed task.
• Sub-agent — when a main agent should decide at run time whether a specialized capability is needed. Good for splitting work into named roles the main agent calls only when relevant.

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Connects to

• Upstream — User Input nodes feeding the prompt or parameters; other nodes producing text/media the model should act on; Tool nodes and Sub-agents into the tools input.
• Downstream — the next node in the flow consumes the Agent’s output. A Sub-agent instead feeds its tool_out into a main Agent.

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Notes / limits

• Tools input accepts multiple connections; the model’s output, prompt, and parameters depend on the selected model.
• Structured output replaces the default free-text output with named field handles.
• A structured list creates multiple output items only when it is the schema’s sole field.
• An Agent can run by itself; a Sub-agent cannot and must be connected to a parent Agent.
• Max sub-agent depth is 5.
• Tool names must be unique per parent agent.
• No sub-agent cycles — the call graph must stay acyclic, like the rest of the canvas (no cycles or self-connections).
• Connection compatibility follows the standard rules: exact-type matches connect, any connects to anything except tool-list, tool-list only connects to tool-list, and media types can feed a file target.

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Next steps