Capacity Planning

Handles the math and structure for figuring out how many people you need and whether your team can actually deliver what's been promised. Includes Python examples for calculating available hours after meetings and overhead, tracking absences, and spotting skill bottlenecks before they become problems. The 85% utilization rule and contingency buffers are sensible defaults that acknowledge reality instead of pretending everyone codes 40 hours a week. Most useful during quarterly planning or when you're trying to explain to stakeholders why adding one more project means something else has to slip. The reference guides cover forecasting and resource leveling if you need more depth than the basic capacity calculator.

skills.sh installs: 444
GitHub stars: 379
last updated: Aug 21, 2026

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Install

$ npx -y skills add aj-geddes/useful-ai-prompts --skill capacity-planning --agent claude-code

Installs into .claude/skills of the current project.

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Overview

Capacity planning ensures teams have sufficient resources to deliver work at sustainable pace, prevents burnout, and enables accurate commitment to stakeholders.

When to Use

Annual or quarterly planning cycles
Allocating people to projects
Adjusting team size
Planning for holidays and absences
Forecasting resource needs
Balancing multiple projects
Identifying bottlenecks

Quick Start

Minimal working example:

# Team capacity calculation and planning

class CapacityPlanner:
    # Standard work hours per week
    STANDARD_WEEK_HOURS = 40

    # Activities that reduce available capacity
    OVERHEAD_HOURS = {
        'meetings': 5,           # standups, 1-on-1s, planning
        'training': 2,           # learning new tech
        'administrative': 2,     # emails, approvals
        'support': 2,            # helping teammates
        'contingency': 2         # interruptions, emergencies
    }

SKILL.md on GitHub