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Architecture guidance for AI Doctor Assistant
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Based on SOC occupation classification
Generate a structured pre-consultation patient briefing. Use when the physician asks for a briefing, a pre-consultation summary, or sends /briefing.
Search the live web or read a specific web page for recency-sensitive clinical information — drug recalls, newly published guidance, FDA/EMA safety communications — that the local clinical guidelines corpus does not cover. Use when the physician asks to "search the web", "look up the latest", or asks about something the guidelines search returned no results for.
Claude Agent SDK patterns and best practices
Code review and refactoring guidelines
FastAPI backend patterns for AI Doctor Assistant
React frontend development patterns for AI Doctor Assistant
| name | staff-architect |
| description | Architecture guidance for AI Doctor Assistant |
┌─────────────────────────────────────────────────┐
│ Two-Step Briefing Flow │
├─────────────────────────────────────────────────┤
│ │
│ STEP 1: Deterministic Rules (Python) │
│ - FlagAnalyzer.apply_rules(patient) │
│ - Returns: List[Flag] (100% deterministic) │
│ - Source: "rule" │
│ │
│ STEP 2: AI Synthesis (Claude Agent SDK) │
│ - BriefingAgent.generate(patient, rule_flags) │
│ - Returns: PatientBriefing (Pydantic validated)│
│ - AI insights: source="ai" │
│ │
└─────────────────────────────────────────────────┘
| Benefit | Explanation |
|---|---|
| Auditability | Can prove which flags came from rules vs AI |
| Testability | Unit test rules separately, mock agent for integration |
| Reliability | Rules are 100% deterministic (critical for healthcare) |
| Traceability | Clear separation: source: "rule" vs source: "ai" |
Frontend → API → Service → Agent → Tools
↓
Rule Engine
/api/v1/...Keep services loosely coupled
Prefer explicit over implicit
Don't over-engineer
Healthcare Context