# Task Manager Agent — Personal AI OS

Automatically turns emails and meeting notes into prioritized, synced tasks.

## What it does

| Capability | Detail |
|---|---|
| **Email → Tasks** | Scans inbox every 15 min, extracts actionable items via Groq |
| **Meeting → Tasks** | Parses Google Calendar descriptions for action items and follow-ups |
| **Prioritization** | LLM scores each task 1–10 using urgency + impact + effort |
| **Deduplication** | Never creates the same task twice |
| **Sync** | Pushes to Notion DB and/or Todoist |
| **Digest** | Sends a formatted email + optional WhatsApp summary |
| **Triggers** | New email detection (polling) + daily 9 AM scheduled sync |

---

## File structure

```
task_manager_agent/
├── main_agent.py       # Orchestrator, scheduler, email watcher
├── data_fetcher.py     # Gmail + Calendar + existing task fetch
├── llm.py              # Groq extraction + prioritization prompts
├── task_store.py       # Local JSON persistence + dedup
├── delivery.py         # Email SMTP, WhatsApp, Notion, Todoist
├── .env.example        # All env vars with explanations
├── requirements.txt
└── README.md
```

---

## Setup

### 1. Install dependencies
```bash
pip install -r requirements.txt
```

### 2. Configure environment
```bash
cp .env.example .env
# Edit .env with your credentials
```

### 3. Google credentials
Share the same `credentials.json` and `token.json` from your earlier agents.
The agent needs scopes:
- `gmail.readonly`
- `calendar.readonly`

### 4. Notion Database setup

Create a Notion database with these properties:

| Property | Type |
|---|---|
| Name | Title |
| Status | Select: `To Do`, `In Progress`, `Done` |
| Priority | Select: `Critical`, `High`, `Medium`, `Low` |
| Due Date | Date |
| Category | Select: `Work`, `Personal`, `Admin`, `Communication`, `Research`, `Finance`, `Health`, `Other` |
| Source | Rich Text |
| Priority Score | Number |
| Notes | Rich Text |

Copy the DB ID from the Notion URL:
`https://notion.so/your-workspace/`**`THIS-IS-YOUR-DB-ID`**`?v=...`

### 5. Run
```bash
python main_agent.py
```

On startup the agent runs immediately, then enters the continuous loop:
- Email watcher polls every `EMAIL_POLL_INTERVAL_MINUTES` minutes
- Full sync fires daily at **09:00**

---

## How prioritization works

The LLM scores each task using four axes:

```
Priority Score (1-10) = f(urgency, impact, effort, dependencies)
```

| Score | Label | Example |
|---|---|---|
| 9–10 | Critical | "Contract due tomorrow, client blocked" |
| 7–8 | High | "Respond to investor by Friday" |
| 5–6 | Medium | "Update project docs" |
| 1–4 | Low | "Read that article someone forwarded" |

---

## Cron alternative

To run via system cron instead of the built-in scheduler:

```cron
# Daily 9 AM sync
0 9 * * * cd /path/to/task_manager_agent && python -c "from main_agent import run_task_extraction_pipeline; run_task_extraction_pipeline('cron_9am')"

# Email polling every 15 min
*/15 * * * * cd /path/to/task_manager_agent && python -c "from main_agent import run_task_extraction_pipeline; run_task_extraction_pipeline('email_poll')"
```

---

## Agent position in Personal AI OS

```
01 ✅ Daily Planner Agent
02 ✅ Email Agent
03 ✅ Meeting Prep Agent
04 ✅ End-of-Day Review Agent
05 ✅ Task Manager Agent  ← YOU ARE HERE
06    Research Agent
07    Finance Agent
08    LinkedIn Agent
09    Knowledge Agent
10    Master Orchestrator (Mem0 + LangGraph)
```

The Master Orchestrator will call `run_task_extraction_pipeline()` directly
and read from `TaskStore` to feed task context into other agents.