Skill: time-management

What I do

I help manage work sessions effectively through timeboxing, focus techniques, duration estimation, and knowing when to take breaks. I provide duration data to token-cost-estimation for accurate planning.

When to use me

• When planning work session duration
• When needing to timebox tasks
• When focus is degrading
• When estimating how long tasks will take
• When token-cost-estimation needs duration multipliers

Core principles

1. Timebox ruthlessly - Set time limits, respect them
2. Focus in blocks - Deep work needs uninterrupted time
3. Breaks restore efficiency - Fatigue increases token usage
4. Estimate duration explicitly - Don't drift without awareness
5. Know when to stop - Diminishing returns are real

Duration Estimation

Task Duration Categories

Duration Impact on Tokens

Longer sessions increase token usage due to:

• Context rebuilding after breaks
• Fatigue-induced inefficiency
• Increased iteration cycles
• Re-reading previous work

Efficiency formula:

Effective tokens = Base tokens × Duration multiplier
Duration multiplier:
  - Short: 1.0x
  - Medium: 1.3x
  - Long: 1.7x
  - Extended: 2.0x+

Timeboxing Patterns

Sprint Timeboxing

• Set explicit time limit before starting
• At 80% of timebox: assess progress
• At 100%: stop and evaluate, don't extend automatically

Break Recommendations

Breaks maintain token efficiency - Fatigued reasoning uses more tokens for same output.

Anti-patterns to avoid

• ❌ Open-ended sessions without time limits
• ❌ Skipping breaks to "save time" (increases total tokens)
• ❌ Not estimating duration before starting
• ❌ Extending timeboxes repeatedly
• ❌ Ignoring fatigue signals

KB Reference

~/vaults/baphled/3. Resources/Knowledge Base/AI Development System/Skills/Workflow-Orchestration/Time Management.md

Related skills

• token-cost-estimation - Uses duration for token estimates
• estimation - Duration is a form of estimation
• scope-management - Scope affects duration
• task-tracker - Track time per task