Daily Oracle (Automated)
This skill is designed to run as a background process (Cron Job). It wakes up, analyzes the user's digital footprint, generates a prediction, pushes the notification, and then terminates.
⚠️ PRIVACY NOTICE: This skill processes highly sensitive personal data. All analysis must be performed within the local LLM context. No data is to be sent to third-party logging services.
Execution Routine
1. Initialization & Anti-Ban Jitter
- Context: Since this task is triggered by a precise Cron timer (e.g., exactly 08:00:00), immediate execution creates a detectable bot pattern.
- Action: Generate a random integer between 120 and 900 (seconds).
- Wait: Sleep for that duration before making any network requests.
```bash
sleep $(( RANDOM % 780 + 120 ))
```
2. Silent Data Gathering
A. Calendar Context
- Action: Read the local calendar for today's agenda (00:00 to 23:59).
- Tool Usage: Use
calendar-access or CLI equivalents (e.g., icalBuddy on macOS).
- _Prompt_: "Summarize my calendar events for today from 00:00 to 23:59. Focus on constraints (meetings) and opportunities (free blocks)."
B. Social Context (Headless)
- Action: Open a headless browser session using _existing_ cookies.
- Target: Scan "Close Friends" or specific mutuals who appear in the user's recent calendar/messages.
- Safety: Limit scrolling to max 5 posts/stories. Abort immediately if login is requested to prevent session flagging.
- Data Extraction: Screenshot or scrape text from the first viewport of specific curated URLs (e.g.,
instagram.com/direct/inbox/).
C. Communications (iMessage/Local DB)
- Action: Read the last 50 messages from the local
chat.db.
- Query:
```sql
SELECT
text,
datetime(date/1000000000 + 978307200, 'unixepoch', 'localtime') as date_sent
FROM message
WHERE date_sent > datetime('now', '-24 hours')
ORDER BY date DESC
LIMIT 50;
```
- Filtering: Look for intent keywords: "tomorrow", "gym", "coffee", "meet", "lunch", "tonight".
D. System Signals
- Action: Check
~/Downloads for recent files.
```bash
find ~/Downloads -type f -mtime -1 -print
```
- Inference: Determine active deliverables or recent interests based on file types (e.g., PDFs vs. Images).
3. The Oracle's Inference
- Synthesize: Combine the hard data (Calendar: "Gym at 5pm") with soft data (Social: "Amy posted about coffee").
- Predict: Formulate a single, high-confidence sentence in the future tense.
- Tone: Insightful but grounded. Example: _"You will meet Amy at the gym today, and she will likely suggest getting coffee after workout because she posted about craving caffeine"_
4. Push Notification (Critical)
- Context: The user is likely not looking at the terminal or chat window.
- Action: Use the system's primary notification tool.
- _macOS_:
osascript -e 'display notification "Your prediction..." with title "Daily Oracle"'
- _Linux_:
notify-send "Daily Oracle" "Your prediction..."
- Format:
> 🔮 Daily Oracle: [Your Prediction Here]
Constraints & Safety
- One-Shot Execution: This process must run from start to finish without pausing for user input.
- Failure Mode: If data is insufficient to make a specific prediction, fall back to a generic personalized wellness tip based on the weather. Do NOT fail silently.
- Data Hygiene: Clearly wipe the temporary context/memory of the gathered data once the prediction is sent.
- Silence on Sources: The output message must strictly contain the _prediction_ and subtle reason for prediction. Do not list the data sources in the notification.