personal-assistant

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npx skills add ailabs-393/ai-labs-claude-skills --skill personal-assistant

Documentation

SKILL.md

npx skills add ...

Documentation

SKILL.md

This skill should be used whenever users request personal assistance tasks such as schedule management, task tracking, reminder setting, habit monitoring, productivity advice, time management, or any query requiring personalized responses based on user preferences and context. On first use, collects comprehensive user information including schedule, working habits, preferences, goals, and routines. Maintains an intelligent database that automatically organizes and prioritizes information, keeping relevant data and discarding outdated context.

npx skills add ailabs-393/ai-labs-claude-skills --skill personal-assistant

Documentation

SKILL.mdView source

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database that adapts to user needs, automatically managing data retention to keep relevant information while discarding outdated content.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:

import sys
import json
sys.path.append('[SKILL_DIR]/scripts')
from assistant_db import save_profile
 
profile = {
    "name": "User's name",
    "preferred_name": "How they like to be addressed",
    "timezone": "America/New_York",
    "location": "New York, USA",
    "work_hours": {
        "start": "09:00",
        "end": "17:00",
        "flexible": True
    },
    "preferences": {
        "communication_style": "concise",
        "reminder_style": "gentle",
        "task_organization": "by_priority"
    },
    "goals": {
        "short_term": ["list", "of", "goals"],
        "long_term": ["list", "of", "goals"]
    },
    "routines": {
        "morning": "Description of morning routine",
        "evening": "Description of evening routine"
    },
    "working_style": "morning person",
    "recurring_commitments": [
        {"title": "Team standup", "frequency": "daily", "time": "10:00"},
        {"title": "Gym", "frequency": "3x per week", "preferred_times": ["18:00", "19:00"]}
    ]
}
 
save_profile(profile)

Replace [SKILL_DIR] with the actual skill directory path.

Confirmation:

Perfect! I've saved your profile. From now on, I'll provide personalized assistance based on your schedule, preferences, and goals. I'll help you stay organized, track your tasks, and optimize your time.

You can update your profile anytime by asking me to modify your preferences or schedule.

Step 3: Load Profile and Context

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

# Check profile status
python3 scripts/assistant_db.py has_profile
 
# Get full profile
python3 scripts/assistant_db.py get_profile
 
# Get current tasks
python3 scripts/assistant_db.py get_tasks
 
# Get schedule
python3 scripts/assistant_db.py get_schedule
 
# Get context and notes
python3 scripts/assistant_db.py get_context
 
# Get quick summary
python3 scripts/assistant_db.py summary

Or use Python imports for more control:

import sys
sys.path.append('[SKILL_DIR]/scripts')
from assistant_db import get_profile, get_tasks, get_schedule, get_context
 
profile = get_profile()
tasks = get_tasks()
schedule = get_schedule()
context = get_context()

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

User: "I need to finish the quarterly report"

Claude: [Loads profile - finds: works 9-5, morning person, prefers focused blocks]

I'll add that to your tasks. Based on your preference for morning work, I recommend
scheduling this during your 9-11am block tomorrow when you're most productive.

The report is due when? I'll set an appropriate priority and reminder.

[Adds task with context-aware details]

Scenario 2: Schedule Conflict

User: "Can I schedule a dentist appointment at 10am Tuesday?"

Claude: [Checks schedule - finds: Team standup at 10am daily]

I notice you have your daily team standup at 10am. Would you like to:
1. Schedule the dentist for 11am instead
2. Move your standup for that day
3. Choose a different day entirely

What works best for you?

Scenario 3: Goal-Aligned Suggestion

User: "What should I focus on this week?"

Claude: [Loads profile - finds short-term goal: "Learn Python"]

Based on your goal to learn Python, I recommend dedicating 3-4 hours this week to:
1. Tuesday 7-8pm: Python tutorial (after gym, before evening routine)
2. Thursday 7-8pm: Practice exercises
3. Saturday 10-12pm: Build a small project

This fits your schedule and keeps you on track for your 3-month learning goal.
Shall I add these to your calendar?

Step 5: Task Management Operations

Use the task management system for organizing user tasks:

Adding Tasks:

import sys
sys.path.append('[SKILL_DIR]/scripts')
from assistant_db import add_task, add_context
 
task = {
    "title": "Complete quarterly report",
    "description": "Q4 financial analysis",
    "priority": "high",  # high, medium, low
    "category": "work",
    "due_date": "2025-11-15",
    "estimated_time": "3 hours"
}
 
add_task(task)
add_context("interaction", "Added Q4 report task", "normal")

Quick Task Operations via CLI:

# List all tasks in formatted view
python3 scripts/task_helper.py list
 
# Add a quick task
python3 scripts/task_helper.py add "Buy groceries" medium "2025-11-08" personal
 
# Complete a task
python3 scripts/task_helper.py complete <task_id>
 
# View overdue tasks
python3 scripts/task_helper.py overdue
 
# View today's tasks
python3 scripts/task_helper.py today
 
# View this week's tasks
python3 scripts/task_helper.py week
 
# View tasks by category
python3 scripts/task_helper.py category work

Completing Tasks:

from assistant_db import complete_task
 
complete_task(task_id)

Updating Tasks:

from assistant_db import update_task
 
update_task(task_id, {
    "priority": "urgent",
    "due_date": "2025-11-10"
})

Step 6: Schedule and Event Management

Manage calendar events and recurring commitments:

Adding Events:

from assistant_db import add_event
 
# One-time event
event = {
    "title": "Dentist appointment",
    "date": "2025-11-12",
    "time": "14:00",
    "duration": "1 hour",
    "location": "Downtown Dental",
    "notes": "Bring insurance card"
}
 
add_event(event, recurring=False)
 
# Recurring event
recurring_event = {
    "title": "Team standup",
    "frequency": "daily",
    "time": "10:00",
    "duration": "15 minutes",
    "days": ["Monday", "Tuesday", "Wednesday", "Thursday", "Friday"]
}
 
add_event(recurring_event, recurring=True)

Getting Upcoming Events:

from assistant_db import get_events
 
# Get events for next 7 days
upcoming = get_events(days_ahead=7)
 
# Get events for next 30 days
monthly = get_events(days_ahead=30)

Step 7: Context Management and Memory

Maintain context for continuity and personalized assistance:

Adding Context:

from assistant_db import add_context
 
# Track an interaction
add_context("interaction", "User mentioned struggling with morning productivity", "normal")
 
# Add an important note (kept indefinitely)
add_context("note", "User prefers written communication over calls for work matters", "high")
 
# Add temporary context (auto-cleaned after 7 days)
add_context("temporary", "Currently working on project X deadline next week", "normal")

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:

from assistant_db import get_context
 
# Get all context
all_context = get_context()
 
# Get specific type
interactions = get_context("recent_interactions")
notes = get_context("important_notes")
temp = get_context("temporary_context")

Step 8: Intelligent Data Cleanup

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

# Clean up data older than 30 days (default)
python3 scripts/assistant_db.py cleanup
 
# Clean up with custom retention period
python3 scripts/assistant_db.py cleanup 60

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:

from assistant_db import get_profile, save_profile
 
# Load current profile
profile = get_profile()
 
# Update specific fields
profile["work_hours"]["start"] = "08:00"
profile["preferences"]["reminder_style"] = "firm"
 
# Save updated profile
save_profile(profile)

Or update schedule information:

from assistant_db import get_schedule, save_schedule
 
schedule = get_schedule()
schedule["working_hours"]["Friday"] = {"start": "09:00", "end": "15:00"}
save_schedule(schedule)

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

User: "Help me organize my week"

Claude: [Checks profile - finds none]

I'd love to help you organize your week! To provide the most personalized assistance,
let me first learn about your schedule and preferences. This will only take a few minutes.

What's your typical work schedule like? For example, do you work 9-5, have flexible
hours, or something else?

[Proceeds through profile setup]

Great! Now let me look at your week and help you organize it effectively...

Example 2: Task Management

User: "I have so many things to do, I'm overwhelmed"

Claude: [Loads tasks - finds 15 pending tasks, 8 with no due date]

I can see you have 15 pending tasks. Let me help you prioritize based on your goals
and schedule.

High Priority (Due Soon):
1. Quarterly report - Due Tuesday (aligns with your career goals)
2. Client presentation - Due Thursday

Medium Priority (This Week):
3. Code review - No deadline but good for Friday afternoon
4. Team feedback - Due next Monday

Let's start with the top 2. Your morning blocks (9-11am) work best for focused work
like the quarterly report. Shall I schedule it for tomorrow morning?

[Helps organize and prioritize based on profile]

Example 3: Schedule Optimization

User: "I want to start exercising regularly"

Claude: [Loads profile - finds: evening person, free 18:00-19:00 most days]

Based on your schedule and preferences, I can see you're typically free between
6-7pm on weekdays. This aligns well with your peak energy time in the evenings.

I recommend:
- Monday, Wednesday, Friday: 18:00-19:00 (gym or home workout)
- Start with 30-minute sessions

This gives you recovery days and doesn't conflict with your Tuesday team dinner
or Thursday book club.

Shall I add these as recurring events to your calendar?

Example 4: Returning User with Context

User: "How's my progress on learning Python?"

Claude: [Loads context - finds: Goal to learn Python, completed 4 tutorial sessions,
last one was 5 days ago]

You're making good progress! You've completed 4 Python tutorial sessions over the
past 3 weeks. However, I notice it's been 5 days since your last session.

To maintain momentum toward your 3-month goal, let's schedule your next session.
Your usual Thursday 7pm slot is open tomorrow. Does that work?

Also, you're at the point where building a small project would be valuable. What
interests you - a web scraper, a to-do app, or something else?

Example 5: Preference Update

User: "I've started a new job, my schedule has changed"

Claude: [Loads current profile]

Congratulations on the new job! Let me update your profile with your new schedule.

What are your new working hours? And have any of your recurring commitments changed?

[Collects updated information and saves]

Perfect! I've updated your profile with your new 8-4 schedule and remote work setup.
I'll adjust all my suggestions accordingly. Your morning productivity block is now
8-10am instead of 9-11am.

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:

# Profile management
python3 scripts/assistant_db.py has_profile
python3 scripts/assistant_db.py get_profile
 
# Task management
python3 scripts/assistant_db.py get_tasks
 
# Schedule management
python3 scripts/assistant_db.py get_schedule
 
# Context management
python3 scripts/assistant_db.py get_context
 
# Utilities
python3 scripts/assistant_db.py summary      # Quick overview
python3 scripts/assistant_db.py cleanup [days]  # Clean old data
python3 scripts/assistant_db.py export       # Export all data
python3 scripts/assistant_db.py reset        # Reset everything

Task Helper Commands:

python3 scripts/task_helper.py list
python3 scripts/task_helper.py add <title> [priority] [due_date] [category]
python3 scripts/task_helper.py complete <task_id>
python3 scripts/task_helper.py overdue
python3 scripts/task_helper.py today
python3 scripts/task_helper.py week
python3 scripts/task_helper.py category <name>

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:

{
  "initialized": true,
  "name": "John Doe",
  "preferred_name": "John",
  "timezone": "America/New_York",
  "location": "New York, USA",
  "work_hours": {
    "start": "09:00",
    "end": "17:00",
    "flexible": true
  },
  "preferences": {
    "communication_style": "concise",
    "reminder_style": "gentle",
    "task_organization": "by_priority"
  },
  "goals": {
    "short_term": ["Learn Python", "Run 5K"],
    "long_term": ["Career advancement", "Financial independence"]
  },
  "working_style": "morning person"
}

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

npx skills add ailabs-393/ai-labs-claude-skills --skill personal-assistant

Documentation

SKILL.md

npx skills add ailabs-393/ai-labs-claude-skills --skill personal-assistant

Documentation

SKILL.mdView source

Personal Assistant

Overview

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:

import sys
import json
sys.path.append('[SKILL_DIR]/scripts')
from assistant_db import save_profile
 
profile = {
    "name": "User's name",
    "preferred_name": "How they like to be addressed",
    "timezone": "America/New_York",
    "location": "New York, USA",
    "work_hours": {
        "start": "09:00",
        "end": "17:00",
        "flexible": True
    },
    "preferences": {
        "communication_style": "concise",
        "reminder_style": "gentle",
        "task_organization": "by_priority"
    },
    "goals": {
        "short_term": ["list", "of", "goals"],
        "long_term": ["list", "of", "goals"]
    },
    "routines": {
        "morning": "Description of morning routine",
        "evening": "Description of evening routine"
    },
    "working_style": "morning person",
    "recurring_commitments": [
        {"title": "Team standup", "frequency": "daily", "time": "10:00"},
        {"title": "Gym", "frequency": "3x per week", "preferred_times": ["18:00", "19:00"]}
    ]
}
 
save_profile(profile)

Replace [SKILL_DIR] with the actual skill directory path.

Confirmation:

Perfect! I've saved your profile. From now on, I'll provide personalized assistance based on your schedule, preferences, and goals. I'll help you stay organized, track your tasks, and optimize your time.

You can update your profile anytime by asking me to modify your preferences or schedule.

Step 3: Load Profile and Context

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

# Check profile status
python3 scripts/assistant_db.py has_profile
 
# Get full profile
python3 scripts/assistant_db.py get_profile
 
# Get current tasks
python3 scripts/assistant_db.py get_tasks
 
# Get schedule
python3 scripts/assistant_db.py get_schedule
 
# Get context and notes
python3 scripts/assistant_db.py get_context
 
# Get quick summary
python3 scripts/assistant_db.py summary

Or use Python imports for more control:

import sys
sys.path.append('[SKILL_DIR]/scripts')
from assistant_db import get_profile, get_tasks, get_schedule, get_context
 
profile = get_profile()
tasks = get_tasks()
schedule = get_schedule()
context = get_context()

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

User: "I need to finish the quarterly report"

Claude: [Loads profile - finds: works 9-5, morning person, prefers focused blocks]

I'll add that to your tasks. Based on your preference for morning work, I recommend
scheduling this during your 9-11am block tomorrow when you're most productive.

The report is due when? I'll set an appropriate priority and reminder.

[Adds task with context-aware details]

Scenario 2: Schedule Conflict

User: "Can I schedule a dentist appointment at 10am Tuesday?"

Claude: [Checks schedule - finds: Team standup at 10am daily]

I notice you have your daily team standup at 10am. Would you like to:
1. Schedule the dentist for 11am instead
2. Move your standup for that day
3. Choose a different day entirely

What works best for you?

Scenario 3: Goal-Aligned Suggestion

User: "What should I focus on this week?"

Claude: [Loads profile - finds short-term goal: "Learn Python"]

Based on your goal to learn Python, I recommend dedicating 3-4 hours this week to:
1. Tuesday 7-8pm: Python tutorial (after gym, before evening routine)
2. Thursday 7-8pm: Practice exercises
3. Saturday 10-12pm: Build a small project

This fits your schedule and keeps you on track for your 3-month learning goal.
Shall I add these to your calendar?

Step 5: Task Management Operations

Use the task management system for organizing user tasks:

Adding Tasks:

import sys
sys.path.append('[SKILL_DIR]/scripts')
from assistant_db import add_task, add_context
 
task = {
    "title": "Complete quarterly report",
    "description": "Q4 financial analysis",
    "priority": "high",  # high, medium, low
    "category": "work",
    "due_date": "2025-11-15",
    "estimated_time": "3 hours"
}
 
add_task(task)
add_context("interaction", "Added Q4 report task", "normal")

Quick Task Operations via CLI:

# List all tasks in formatted view
python3 scripts/task_helper.py list
 
# Add a quick task
python3 scripts/task_helper.py add "Buy groceries" medium "2025-11-08" personal
 
# Complete a task
python3 scripts/task_helper.py complete <task_id>
 
# View overdue tasks
python3 scripts/task_helper.py overdue
 
# View today's tasks
python3 scripts/task_helper.py today
 
# View this week's tasks
python3 scripts/task_helper.py week
 
# View tasks by category
python3 scripts/task_helper.py category work

Completing Tasks:

from assistant_db import complete_task
 
complete_task(task_id)

Updating Tasks:

from assistant_db import update_task
 
update_task(task_id, {
    "priority": "urgent",
    "due_date": "2025-11-10"
})

Step 6: Schedule and Event Management

Manage calendar events and recurring commitments:

Adding Events:

from assistant_db import add_event
 
# One-time event
event = {
    "title": "Dentist appointment",
    "date": "2025-11-12",
    "time": "14:00",
    "duration": "1 hour",
    "location": "Downtown Dental",
    "notes": "Bring insurance card"
}
 
add_event(event, recurring=False)
 
# Recurring event
recurring_event = {
    "title": "Team standup",
    "frequency": "daily",
    "time": "10:00",
    "duration": "15 minutes",
    "days": ["Monday", "Tuesday", "Wednesday", "Thursday", "Friday"]
}
 
add_event(recurring_event, recurring=True)

Getting Upcoming Events:

from assistant_db import get_events
 
# Get events for next 7 days
upcoming = get_events(days_ahead=7)
 
# Get events for next 30 days
monthly = get_events(days_ahead=30)

Step 7: Context Management and Memory

Maintain context for continuity and personalized assistance:

Adding Context:

from assistant_db import add_context
 
# Track an interaction
add_context("interaction", "User mentioned struggling with morning productivity", "normal")
 
# Add an important note (kept indefinitely)
add_context("note", "User prefers written communication over calls for work matters", "high")
 
# Add temporary context (auto-cleaned after 7 days)
add_context("temporary", "Currently working on project X deadline next week", "normal")

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:

from assistant_db import get_context
 
# Get all context
all_context = get_context()
 
# Get specific type
interactions = get_context("recent_interactions")
notes = get_context("important_notes")
temp = get_context("temporary_context")

Step 8: Intelligent Data Cleanup

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

# Clean up data older than 30 days (default)
python3 scripts/assistant_db.py cleanup
 
# Clean up with custom retention period
python3 scripts/assistant_db.py cleanup 60

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:

from assistant_db import get_profile, save_profile
 
# Load current profile
profile = get_profile()
 
# Update specific fields
profile["work_hours"]["start"] = "08:00"
profile["preferences"]["reminder_style"] = "firm"
 
# Save updated profile
save_profile(profile)

Or update schedule information:

from assistant_db import get_schedule, save_schedule
 
schedule = get_schedule()
schedule["working_hours"]["Friday"] = {"start": "09:00", "end": "15:00"}
save_schedule(schedule)

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

User: "Help me organize my week"

Claude: [Checks profile - finds none]

I'd love to help you organize your week! To provide the most personalized assistance,
let me first learn about your schedule and preferences. This will only take a few minutes.

What's your typical work schedule like? For example, do you work 9-5, have flexible
hours, or something else?

[Proceeds through profile setup]

Great! Now let me look at your week and help you organize it effectively...

Example 2: Task Management

User: "I have so many things to do, I'm overwhelmed"

Claude: [Loads tasks - finds 15 pending tasks, 8 with no due date]

I can see you have 15 pending tasks. Let me help you prioritize based on your goals
and schedule.

High Priority (Due Soon):
1. Quarterly report - Due Tuesday (aligns with your career goals)
2. Client presentation - Due Thursday

Medium Priority (This Week):
3. Code review - No deadline but good for Friday afternoon
4. Team feedback - Due next Monday

Let's start with the top 2. Your morning blocks (9-11am) work best for focused work
like the quarterly report. Shall I schedule it for tomorrow morning?

[Helps organize and prioritize based on profile]

Example 3: Schedule Optimization

User: "I want to start exercising regularly"

Claude: [Loads profile - finds: evening person, free 18:00-19:00 most days]

Based on your schedule and preferences, I can see you're typically free between
6-7pm on weekdays. This aligns well with your peak energy time in the evenings.

I recommend:
- Monday, Wednesday, Friday: 18:00-19:00 (gym or home workout)
- Start with 30-minute sessions

This gives you recovery days and doesn't conflict with your Tuesday team dinner
or Thursday book club.

Shall I add these as recurring events to your calendar?

Example 4: Returning User with Context

User: "How's my progress on learning Python?"

Claude: [Loads context - finds: Goal to learn Python, completed 4 tutorial sessions,
last one was 5 days ago]

You're making good progress! You've completed 4 Python tutorial sessions over the
past 3 weeks. However, I notice it's been 5 days since your last session.

To maintain momentum toward your 3-month goal, let's schedule your next session.
Your usual Thursday 7pm slot is open tomorrow. Does that work?

Also, you're at the point where building a small project would be valuable. What
interests you - a web scraper, a to-do app, or something else?

Example 5: Preference Update

User: "I've started a new job, my schedule has changed"

Claude: [Loads current profile]

Congratulations on the new job! Let me update your profile with your new schedule.

What are your new working hours? And have any of your recurring commitments changed?

[Collects updated information and saves]

Perfect! I've updated your profile with your new 8-4 schedule and remote work setup.
I'll adjust all my suggestions accordingly. Your morning productivity block is now
8-10am instead of 9-11am.

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:

# Profile management
python3 scripts/assistant_db.py has_profile
python3 scripts/assistant_db.py get_profile
 
# Task management
python3 scripts/assistant_db.py get_tasks
 
# Schedule management
python3 scripts/assistant_db.py get_schedule
 
# Context management
python3 scripts/assistant_db.py get_context
 
# Utilities
python3 scripts/assistant_db.py summary      # Quick overview
python3 scripts/assistant_db.py cleanup [days]  # Clean old data
python3 scripts/assistant_db.py export       # Export all data
python3 scripts/assistant_db.py reset        # Reset everything

Task Helper Commands:

python3 scripts/task_helper.py list
python3 scripts/task_helper.py add <title> [priority] [due_date] [category]
python3 scripts/task_helper.py complete <task_id>
python3 scripts/task_helper.py overdue
python3 scripts/task_helper.py today
python3 scripts/task_helper.py week
python3 scripts/task_helper.py category <name>

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:

{
  "initialized": true,
  "name": "John Doe",
  "preferred_name": "John",
  "timezone": "America/New_York",
  "location": "New York, USA",
  "work_hours": {
    "start": "09:00",
    "end": "17:00",
    "flexible": true
  },
  "preferences": {
    "communication_style": "concise",
    "reminder_style": "gentle",
    "task_organization": "by_priority"
  },
  "goals": {
    "short_term": ["Learn Python", "Run 5K"],
    "long_term": ["Career advancement", "Financial independence"]
  },
  "working_style": "morning person"
}

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