Harness

The harness is a standard function-calling (agentic) harness around the LLM. It gives the model what it needs to act each turn: the conversation history, the current variables, and the tools it is allowed to call.

The agentic loop

Each turn, the harness runs a simple loop around the LLM:

1. Assemble context: conversation history, variables, and available tools.
2. The LLM reasons, and either responds or calls a tool.
3. If it calls a tool, the harness runs it and feeds the result back.
4. Repeat until the LLM produces a response.

Variables

The harness carries variables through the conversation. Values can also be injected into context (for example from an on-start hook or your backend), so the model always reasons over the right state.

Tools

The model acts through tools. Some are built-in core tools, and you can author your own to extend what the agent can do.