# 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.