detecting-patterns

Pattern Detection Skill

Overview

Detect and analyze patterns in your productivity, habits, energy levels, and behaviors to generate actionable insights for optimization and improvement.

Trigger

• Monthly during life assessment
• Weekly during weekly review
• On-demand when seeking insights
• After significant life changes

Inputs

• Daily logs from memory/daily/
• Weekly reviews from memory/weekly/
• Monthly reviews from memory/monthly/
• Calendar events and meeting data
• Task completion records
• Energy and mood tracking data
• Goal progress metrics

Pattern Types

1. Productivity Patterns

What to detect:

• Peak productivity hours (morning/afternoon/evening)
• High-performance days of the week
• Task completion velocity patterns
• Deep work session duration patterns
• Context switching frequency

Analysis approach:

FOR each time_of_day in [morning, afternoon, evening]:
  CALCULATE average_tasks_completed
  CALCULATE average_quality_score
  CALCULATE average_energy_level

FOR each day_of_week:
  CALCULATE completion_rate
  CALCULATE focus_duration
  IDENTIFY recurring_blockers

2. Task Completion Patterns

What to detect:

• Tasks that consistently get done vs. delayed
• Task types that flow easily vs. create resistance
• Completion patterns by context (location, time, people)
• Procrastination triggers
• Task batching effectiveness

Analysis approach:

GROUP tasks BY [type, priority, context]
FOR each group:
  CALCULATE completion_rate
  CALCULATE average_delay
  IDENTIFY success_factors
  DETECT resistance_patterns

3. Meeting Patterns

What to detect:

• Productive vs. draining meeting types
• Optimal meeting times
• Meeting frequency impact on productivity
• Pre/post-meeting energy patterns
• Meeting preparation effectiveness

Analysis approach:

FOR each meeting:
  MEASURE pre_energy vs post_energy
  TRACK post_meeting_productivity
  CATEGORIZE by [type, duration, participants]
  CALCULATE roi_score