aj-geddes/useful-ai-prompts

capacity-planning

Analyze team capacity, plan resource allocation, and balance workload across projects. Forecast staffing needs and optimize team utilization while maintaining sustainable pace.

First seen Jan 21, 2026

Installation

$ npx skills add aj-geddes/useful-ai-prompts --skill capacity-planning

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Repository health

Stars 334
License LICENSE
Default branch main
Open issues 1
Status Active

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 3,083 B
  • docs SUMMARY.md 2,875 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 421 installs

SKILL.md

Capacity Planning

Table of Contents

  • [Overview](#overview)
  • [When to Use](#when-to-use)
  • [Quick Start](#quick-start)
  • [Reference Guides](#reference-guides)
  • [Best Practices](#best-practices)

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
    }

    def __init__(self, team_size, sprint_duration_weeks=2):
        self.team_size = team_size
        self.sprint_duration_weeks = sprint_duration_weeks
        self.members = []

    def calculate_team_capacity(self):
        """Calculate available capacity hours"""
        # Base capacity
        base_hours = self.team_size * self.STANDARD_WEEK_HOURS * self.sprint_duration_weeks

// ... (see reference guides for full implementation)

Reference Guides

Detailed implementations in the references/ directory:

Guide Contents
[Capacity Assessment](references/capacity-assessment.md) Capacity Assessment
[Capacity Planning Template](references/capacity-planning-template.md) Capacity Planning Template
[Resource Leveling](references/resource-leveling.md) Resource Leveling
[Capacity Forecasting](references/capacity-forecasting.md) Capacity Forecasting

Best Practices

✅ DO

  • Plan capacity at 85% utilization (15% buffer)
  • Account for meetings, training, and overhead
  • Include known absences (vacation, holidays)
  • Identify skill bottlenecks early
  • Balance workload fairly across team
  • Review capacity monthly
  • Adjust plans based on actual velocity
  • Cross-train on critical skills
  • Communicate realistic commitments to stakeholders
  • Build contingency for emergencies

❌ DON'T

  • Plan at 100% utilization
  • Ignore meetings and overhead
  • Assign work without checking skills
  • Create overload with continuous surprises
  • Forget about learning/training time
  • Leave capacity planning to last minute
  • Overcommit team consistently
  • Burn out key people
  • Ignore team feedback on workload
  • Plan without considering absences