---

name: daily-oracle version: 1.1.0 description: A background agent that generates a daily life prediction by analyzing local data and social signals. author: https://github.com/Invelene repository: https://github.com/Invelene/Futurizzm/daily-oracle requirements:

• browser-automation

• calendar-access

• local-file-search

• sqlite-access

permissions:

• read: browser_cookies (instagram.com, twitter.com)

• read: local_db (imessage/chat.db)

• read: calendar

• read: filesystem (downloads)

safety_policy: "local-only"

---

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.