Building CareLoop: an autonomous clinical-triage agent where rules decide and AI explains

I created this content for the purposes of entering the All Things Agentic Hackathon. The problem that started it A doctor gets about eight minutes with a patient and, for anyone with a real history, forty pages of scattered records — lab reports, discharge notes, and pharmacy bills from three different clinics. So the history is effectively invisible at the exact moment it matters most. And when the visit ends, nothing follows up: the six-month course lapses at week five, the recheck never gets booked. I wanted to build an agent that closes that loop — one that reads the mess, decides urgency in a way a clinician can actually trust, and handles the follow-up on its own. That became CareLoop , my entry for the All Things Agentic Hackathon (Taskmaster track), built on Gemini, the Google Agent Development Kit (ADK), Cloud Run, and Firestore. The one principle I wouldn't compromise on Rules decide, AI explains. The temptation with an LLM is to let it do everything — including deciding whether a chest-pain patient is urgent. I refused to do that. In CareLoop, a deterministic engine owns every clinical decision: a weighted symptom score plus a red-flag override sets the triage level and routing. It is fully auditable, and it returns byte-identical output on the same input every single time. The LLM's job is strictly language: Reading unstructured documents into a fixed schema — I call it "Gemini extracts, rules merge." Writing the structured result into a plain-language brief a clinician can skim in ten seconds. No language model is ever in the decision path. When a judge asks "why was this Critical?", the answer is a score breakdown they can inspect — not a model's say-so. That single decision shaped the whole architecture. What it actually does CareLoop runs the full loop end to end: Ingest & compact — it reads a patient's documents and merges them into one structured ledger: allergies, chronic conditions, active medications, and lab trends over time. Instead of pushin