How Far Should a Proactive Agent Go?

A proactive agent can notice a real need and still choose an unwelcome response. Timing and the extent of its intervention matter alongside whether it recognized the problem.

Consider a hypothetical university scheduling agent that notices a teaching room is unavailable. Under an assumed university policy, it may inspect approved alternatives and draft a replacement booking, but changing the class location requires the department's confirmation.

If the outage is still being investigated, notifying every student may be premature. Once a replacement is confirmed, another generic warning may provide too little help. Automatically moving the class before confirmation would exceed the delegated scope. The same underlying signal can support different actions as evidence changes.

Evaluate the intervention, including restraint

HALO, by Wenqi Pei and colleagues, separates observation, notification, preparation and execution. Its agents inspect simulated applications, databases and documents before deciding how to respond at a particular checkpoint.

The study contains 8,000 responses from ten models across 400 constructed scenarios. Twenty annotators assess acceptability, with separate timing and intensity diagnoses for rejected interventions. Premature or excessive assistance accounts for 2,188 of the 3,575 rejected responses, or 61.20%, counting each response once when either diagnosis applies.

That denominator matters: the result concerns rejected responses in this designed benchmark, not 61.20% of all proactive actions. Each response receives one annotator's verdict. Checkpoints reset independently, so the evaluation does not measure cumulative disruption or changing user preferences during sustained deployment.

For builders, the useful distinction is that a well-timed action can still go too far, while a restrained response can still omit useful assistance. Doing nothing is sometimes appropriate, but an agent that always waits would miss legitimate opportunities to help.

Put people above routine decisions

Our signals-and-triggers note asks what observation should start work. Our scheduled-agent note asks what remains unfinished. HALO adds another question: what degree of intervention does the current evidence justify?

For WTK's catalog packages, we would want delegated scope to distinguish checking, preparing and committing changes where those distinctions affect the goal. In the scheduling example, finding an alternative room can proceed automatically even when publishing a new location remains an exception.

The relevant assessment would consider useful completed actions, unnecessary interruptions, missed assistance and commitments made beyond authority. An improvement in one measure could conceal a regression in another. Technical permission to use a tool also leaves the question of whether using it now is appropriate.

The goal is fewer routine approvals supported by clearer delegation and dependable exception handling. Human review can define acceptable intervention and examine failures without becoming a mandatory step in every scheduled run.

Source: Pei and colleagues, HALO: Human-Grounded Granular Evaluation of Proactive Agents, arXiv:2610.39086v1, October 29, 2026. The university example and WTK interpretation are ours.