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HOOKS.md

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+# Where the hooks are
+
+## API route registration — `api/main.py`
+
+Lines 10-11: imported `api.routes.routines` and `api.routes.medications`
+Line 16: added both to `ROUTE_MODULES` list so they auto-register on startup
+
+## Bot command registration — `bot/bot.py`
+
+Lines 23-24: imported `bot.commands.routines` and `bot.commands.medications`
+These imports trigger `register_module()` and `register_validator()` at load time,
+which makes the bot's AI parser route "routine" and "medication" interaction types
+to the right handlers.
+
+## Bot command handlers — `bot/commands/routines.py`, `bot/commands/medications.py`
+
+Each file:
+- Defines an async handler (`handle_routine`, `handle_medication`)
+- Defines a JSON validator for the AI parser
+- Calls `register_module()` to hook into the command registry
+- Calls `ai_parser.register_validator()` to hook into parse validation
+
+## Scheduler — `scheduler/daemon.py`
+
+`poll_callback()` now calls three check functions on every tick:
+- `check_medication_reminders()` — sends notifications for doses due now
+- `check_routine_reminders()` — sends notifications for scheduled routines
+- `check_refills()` — warns when medication supply is running low
+
+All three use `core.notifications._sendToEnabledChannels()` to deliver.
+
+## AI config — `ai/ai_config.json`
+
+Updated the `command_parser` system prompt to list the two interaction types
+(`routine`, `medication`) and the fields to extract for each. This is what
+tells the LLM how to parse natural language into the right action structure.
+
+## What's NOT hooked yet (needs implementation)
+
+- `config/schema.sql` — needs tables for routines, routine_steps,
+  routine_sessions, routine_schedules, medications, med_logs
+- The actual body of every API route (all prototyped as `pass`)
+- The actual body of both bot command handlers
+- The three scheduler check functions