This node builds and executes an agent that responds to a single user prompt using a language model and a set of user-defined tools.
Each tool is represented as a KNIME workflow with configurations (e.g., strings, numbers, column selection) and can optionally accept input data tables. While the agent does not have access to raw data, it is informed about available tables through metadata — including column names and types — enabling it to select suitable data for each tool as needed.
When the node is executed, the agent reasons step-by-step to fulfill the user’s prompt. It may call one or more tools in sequence, using the output of one tool as input for another. The model autonomously selects tools and input data based on the prompt and the tools’ names and descriptions. Including clear tool descriptions and example use cases significantly improves the agent’s decision-making.
The entire internal reasoning process — including tool calls and decisions — is captured and available via the conversation output table. This node is designed for non-interactive, one-shot execution. For interactive, multi-turn conversations, use the Chat Agent Prompter node.