A single linear direction in the residual stream dials tool-call rate from near zero to over 90%.

The authors extract a steering direction from the model's existing tool-use preference signal and apply it at inference, producing monotonic control over how often the agent reaches for a tool while keeping invocations valid (arXiv 2608.25198). Open-domain QA accuracy with live tool execution nearly doubled, from 0.29 to 0.56, by tuning the rate rather than the prompt. It generalizes to unseen tools and works across dense, MoE and multimodal architectures. That makes tool-call frequency a deployment knob you set per environment instead of a paragraph you keep rewriting in the system prompt.