chore: initial import

PROMPTS.md

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+# Prompt Reference
+
+This project now ships with ADHD-friendly prompts that tell the assistant how to
+handle reminders, break tasks down, and kick off work sessions. All prompts live
+in `prompts/defaultPrompts.json` (auto-generated from `AppConfig.defaultPromptRecords`
+when missing) and are loaded through `PromptLibrary`.
+
+## Prompt Catalog
+
+| Category  | Name       | Purpose |
+|-----------|------------|---------|
+| `general` | `welcome`  | Greets the user, reminds them they can ask for planning help or reminders, and references the incoming context. |
+| `general` | `fallback` | Keeps momentum if a prompt lookup fails. |
+| `planning`| `breakdown`| Acts as an executive-function coach: empathize, define the outcome, split work into tiny observable steps, and gently ask whether to save the plan or set a reminder. |
+| `reminders` | `schedule` | Confirms reminder details, summarizes them, and—when the user approves—emits a JSON payload that downstream services can consume. |
+| `agentic` | `hourly_review` | Autonomous sweep that reviews notes plus the persistent action list to decide whether to trigger reminders, notes, or other workflows. |
+
+You can add more prompts by dropping additional JSON records into `prompts/`.
+
+## Structured JSON Hooks
+
+The prompts guide the model to output placeholder JSON, similar to how the
+memory subsystem listens for `take_note` actions. Downstream services can
+inspect responses for these payloads and act on them.
+
+### Store a Task Plan
+
+Triggered from the `planning/breakdown` prompt when the user explicitly asks to
+save the plan.
+
+```json
+{
+  "action": "store_task",
+  "task": {
+    "title": "short label",
+    "steps": [
+      {"order": 1, "description": "step detail", "duration": "~5 min"}
+    ],
+    "next_step": "first step text",
+    "context": "<original context>",
+    "status": "not_started"
+  }
+}
+```
+
+### Schedule a Reminder
+
+Triggered from the `reminders/schedule` prompt once timing and content are
+locked in with the user.
+
+```json
+{
+  "action": "schedule_reminder",
+  "reminder": {
+    "title": "short label",
+    "details": "context summary",
+    "trigger": {
+      "type": "datetime | relative | habit",
+      "value": "ISO timestamp or human-friendly string"
+    },
+    "follow_up": "check-in question",
+    "metadata": {
+      "user": "<discord id>",
+      "source": "prompt"
+    }
+  }
+}
+```
+
+### Notes
+
+- Only output one JSON block per response, wrapped in ```json fences, when the
+  user confirms they want the assistant to act.
+- If details are incomplete, stay conversational and gather what you need.
+- Additional actions can be added later by extending the prompt instructions and
+  listening for new `action` values just like `take_note`.
+
+### Agentic Hourly Review
+
+The `agentic/hourly_review` prompt consumes the JSON blob produced by
+`AgenticWorkflow.buildReviewPacket`. It summarizes recent notes plus the
+modifiable action list (cadence, intervals, latest progress) and decides if
+anything needs escalation. When it does, it reuses the same structured actions
+(`take_note`, `store_task`, `schedule_reminder`) so downstream tooling can react
+consistently. When nothing is due it simply acknowledges the sweep.