An AI agent on a phone has access to something a server-side agent doesn’t: the device itself. Calendar events, saved locations, recent contacts, active notifications — all of it is locally available before any network call is made.

The question isn’t whether to use that context. It’s how to resolve it into action parameters without asking the user for information the phone already has, and without silently filling in details the phone only partially knows.

This post covers the context propagation layer in StareBrain — how device state gets resolved into action parameters, how confidence thresholds decide when to auto-fill vs. suggest vs. ask, and what happens when resolution fails.

The Resolution Problem

When a user says “book a slot for my dentist appointment,” the agent needs to resolve:

Which calendar? (probably the default one)

Which slot? (depends on availability)

Which location? (saved as “dentist” in the location store, or needs to be asked)

Which contact to notify, if any?…