Definition
A reward that pays an AI more when its tool use matches the kind of task at hand.
In ToolCUA, a binary reward signaling whether the agent's use (or non-use) of structured tools matched the task's tool-beneficial label, decoupled from raw success to encourage selective tool invocation.
Also called: tool appropriateness