personal-assistant

Personal Assistant

Overview

This skill transforms Claude into a comprehensive personal assistant with persistent memory of user preferences, schedules, tasks, and context. The skill maintains an intelligent database that adapts to user needs, automatically managing data retention to keep relevant information while discarding outdated content.

When to Use This Skill

Invoke this skill for personal assistance queries, including:

Task management and to-do lists
Schedule and calendar management
Reminder setting and tracking
Habit monitoring and productivity tips
Time management and planning
Personal goal tracking
Routine optimization
Preference-based recommendations
Context-aware assistance

Workflow

Step 1: Check for Existing Profile

Before providing any personalized assistance, always check if a user profile exists:

python3 scripts/assistant_db.py has_profile

If the output is "false", proceed to Step 2 (Initial Setup). If "true", proceed to Step 3 (Load Profile and Context).

Step 2: Initial Profile Setup (First Run Only)

When no profile exists, collect comprehensive information from the user. Use a conversational, friendly approach to gather this data.

Essential Information to Collect:

Personal Details
- Name and preferred form of address
- Timezone
- Location (city/country)
Schedule & Working Habits
- Typical work hours
- Work schedule type (9-5, flexible, shift work, etc.)
- Preferred working times (morning person vs night owl)
- Break preferences
- Meeting preferences
Goals & Priorities
- Short-term goals (next 1-3 months)
- Long-term goals (6+ months)
- Priority areas (career, health, relationships, learning, etc.)
- Success metrics
Habits & Routines
- Morning routine
- Evening routine
- Exercise habits
- Sleep schedule
- Meal times
Preferences & Communication Style
- Communication preference (detailed vs concise)
- Reminder style (gentle vs firm)
- Notification preferences
- Task organization style (by priority, category, time, etc.)
Current Commitments
- Recurring commitments (weekly meetings, classes, etc.)
- Regular activities (gym, hobbies, etc.)
- Family or social obligations
Tools & Integration
- Calendar system used (Google, Outlook, Apple, etc.)
- Task management preferences
- Note-taking system

Example Setup Flow:

Hi! I'm your personal assistant. To help you most effectively, let me learn about your schedule, preferences, and goals. This will take just a few minutes.

Let's start with the basics:
1. What's your name, and how would you like me to address you?
2. What timezone are you in?
3. What's your typical work schedule like?

[Continue conversationally through all sections]

Saving the Profile:

After collecting information, save it using Python:

Replace [SKILL_DIR] with the actual skill directory path.

Confirmation:

Step 3: Load Profile and Context

For all personal assistance queries, load the user's data:

Or use Python imports for more control:

Step 4: Provide Personalized Assistance

Apply the loaded profile and context to provide tailored assistance:

Key Principles:

Respect User Preferences
- Use their preferred communication style
- Follow their task organization preferences
- Honor their working hours and routines
Leverage Context
- Reference their goals when suggesting tasks
- Consider their schedule when proposing activities
- Adapt to their working style (morning person, etc.)
Be Proactive
- Suggest task prioritization based on goals
- Remind about recurring commitments
- Flag scheduling conflicts
- Propose routine optimizations
Maintain Context
- Track important interactions
- Remember ongoing projects
- Note temporary context for continuity

Example Applications:

Scenario 1: Task Management

Scenario 2: Schedule Conflict

Scenario 3: Goal-Aligned Suggestion

Step 5: Task Management Operations

Use the task management system for organizing user tasks:

Adding Tasks:

Quick Task Operations via CLI:

Completing Tasks:

Updating Tasks:

Step 6: Schedule and Event Management

Manage calendar events and recurring commitments:

Adding Events:

Getting Upcoming Events:

Step 7: Context Management and Memory

Maintain context for continuity and personalized assistance:

Adding Context:

Context Importance Levels:

"low" - Automatically cleaned up quickly
"normal" - Standard retention (30 days for interactions, 7 days for temporary)
"high" - Kept indefinitely (for important notes) or extended retention

Retrieving Context:

Step 8: Intelligent Data Cleanup

The system automatically manages data retention, but you can trigger manual cleanup:

What Gets Cleaned:

✓ Completed tasks older than retention period
✓ Past one-time events
✓ Old interactions (unless marked high importance)
✓ Temporary context older than 7 days
✗ User profile (never cleaned)
✗ Pending tasks (never cleaned)
✗ Important notes (never cleaned)
✗ Recurring events (never cleaned)

Step 9: Updating User Profile

When users want to update their profile or preferences:

Or update schedule information:

Best Practices

Always Load Context First
- Check profile status before any personalized assistance
- Load relevant data (profile, tasks, schedule) at the start
Be Proactive
- Suggest task prioritization
- Flag scheduling conflicts
- Remind about goals
- Propose optimizations
Respect Preferences
- Honor communication style preferences
- Follow task organization preferences
- Respect working hours and boundaries
Maintain Continuity
- Track important interactions in context
- Reference previous conversations
- Remember ongoing projects
Keep Data Fresh
- Periodically run cleanup (suggest monthly)
- Mark important information appropriately
- Use temporary context for short-term tracking
Provide Value
- Make connections between tasks and goals
- Optimize schedules based on working style
- Offer personalized productivity insights
Update Incrementally
- If user mentions new preferences in conversation, offer to update profile
- Add new commitments to schedule as they arise
- Track context changes naturally

Example Interactions

Example 1: First-Time User

Example 2: Task Management

Example 3: Schedule Optimization

Example 4: Returning User with Context

Example 5: Preference Update

Technical Notes

Data Storage Location: All data is stored in ~/.claude/personal_assistant/:

profile.json - User profile and preferences
tasks.json - Task list and completed tasks
schedule.json - Calendar events and recurring commitments
context.json - Interaction history, notes, and temporary context

Database Commands:

Task Helper Commands:

Data Retention Policy:

User profile: Never auto-deleted
Pending tasks: Never auto-deleted
Completed tasks: Deleted after 30 days (configurable)
One-time past events: Deleted after 30 days (configurable)
Recurring events: Never auto-deleted
Recent interactions: Deleted after 30 days unless marked "high" importance
Important notes: Never auto-deleted
Temporary context: Deleted after 7 days

Profile Data Structure:

Resources

scripts/assistant_db.py

Main database management module providing:

Profile management (get, save, check initialization)
Task CRUD operations (add, update, complete, delete)
Schedule and event management
Context tracking with importance levels
Intelligent data cleanup
Data export and summary functions

scripts/task_helper.py

Convenience script for quick task operations:

Formatted task listings
Quick task addition
Task filtering (overdue, today, this week, by category)
Task completion by ID or title match