home / skills / jeremylongshore / claude-code-plugins-plus-skills / analyzing-capacity-planning

This skill analyzes current utilization, forecasts capacity needs, and recommends scalable strategies to optimize infrastructure growth.

npx playbooks add skill jeremylongshore/claude-code-plugins-plus-skills --skill analyzing-capacity-planning

Review the files below or copy the command above to add this skill to your agents.

Files (7)
SKILL.md
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---
name: analyzing-capacity-planning
description: |
  Execute this skill enables AI assistant to analyze capacity requirements and plan for future growth. it uses the capacity-planning-analyzer plugin to assess current utilization, forecast growth trends, and recommend scaling strategies. use this skill when the u... Use when analyzing code or data. Trigger with phrases like 'analyze', 'review', or 'examine'.
allowed-tools: Read, Write, Edit, Grep, Glob, Bash(cmd:*)
version: 1.0.0
author: Jeremy Longshore <[email protected]>
license: MIT
---
# Capacity Planning Analyzer

This skill provides automated assistance for capacity planning analyzer tasks.

## Overview

This skill empowers Claude to analyze current resource utilization, predict future capacity needs, and provide actionable recommendations for scaling infrastructure. It generates insights into growth trends, identifies potential bottlenecks, and estimates costs associated with capacity expansion.

## How It Works

1. **Analyze Utilization**: The plugin analyzes current CPU, memory, database storage, network bandwidth, and request rate utilization.
2. **Forecast Growth**: Based on historical data, the plugin forecasts future growth trends for key capacity metrics.
3. **Generate Recommendations**: The plugin recommends scaling strategies, including vertical and horizontal scaling options, and estimates associated costs.

## When to Use This Skill

This skill activates when you need to:
- Analyze current infrastructure capacity and identify potential bottlenecks.
- Forecast future resource requirements based on projected growth.
- Develop a capacity roadmap to ensure optimal performance and availability.

## Examples

### Example 1: Planning for Database Growth

User request: "Analyze database capacity and plan for future growth."

The skill will:
1. Analyze current database storage utilization and growth rate.
2. Forecast future storage requirements based on historical trends.
3. Recommend scaling options, such as adding storage or migrating to a larger instance.

### Example 2: Identifying CPU Bottlenecks

User request: "Analyze CPU utilization and identify potential bottlenecks."

The skill will:
1. Analyze CPU utilization trends across different servers and applications.
2. Identify periods of high CPU usage and potential bottlenecks.
3. Recommend scaling options, such as adding more CPU cores or optimizing application code.

## Best Practices

- **Data Accuracy**: Ensure that the data used for analysis is accurate and up-to-date.
- **Metric Selection**: Choose the right capacity metrics to monitor based on your specific application requirements.
- **Regular Monitoring**: Regularly monitor capacity metrics to identify potential issues before they impact performance.

## Integration

This skill can be integrated with other monitoring and alerting tools to provide proactive capacity management. It can also be used in conjunction with infrastructure-as-code tools to automate scaling operations.

## Prerequisites

- Appropriate file access permissions
- Required dependencies installed

## Instructions

1. Invoke this skill when the trigger conditions are met
2. Provide necessary context and parameters
3. Review the generated output
4. Apply modifications as needed

## Output

The skill produces structured output relevant to the task.

## Error Handling

- Invalid input: Prompts for correction
- Missing dependencies: Lists required components
- Permission errors: Suggests remediation steps

## Resources

- Project documentation
- Related skills and commands

Overview

This skill enables the AI assistant to analyze current resource utilization, forecast future capacity needs, and produce actionable scaling recommendations. It focuses on CPU, memory, storage, network, and request-rate metrics to identify bottlenecks and estimate costs for capacity changes. Use it to build a data-driven capacity roadmap that supports planned growth and maintains performance.

How this skill works

The skill ingests historical and current utilization data, then analyzes trends across CPU, memory, database storage, bandwidth, and request rates. It applies forecasting logic to predict future capacity needs and highlights likely bottlenecks. Finally, it generates practical recommendations—vertical and horizontal scaling options, migration suggestions, and cost estimates—along with structured output you can use in planning or automation.

When to use it

  • Assess current infrastructure to find potential bottlenecks before incidents occur
  • Forecast resource needs for a planned product launch, marketing campaign, or user growth period
  • Plan database growth and storage provisioning over time
  • Review CPU or memory trends to decide between optimization vs. scaling
  • Integrate capacity insights into infrastructure-as-code or automation workflows

Best practices

  • Use clean, high-resolution historical metrics for more accurate forecasts
  • Select metrics that match your application patterns (e.g., latency, request rate, queue depth)
  • Run analyses regularly and after major releases or traffic changes
  • Combine capacity forecasts with cost estimates to evaluate scaling trade-offs
  • Validate recommendations with short-term load tests or pilot deployments

Example use cases

  • Analyze database storage trends and forecast required capacity for the next 12 months
  • Review CPU utilization across a fleet to identify overloaded instances and recommend resizing or sharding
  • Forecast network and bandwidth needs for an upcoming feature rollout and propose CDN or edge strategies
  • Produce a capacity roadmap that maps growth milestones to scaling actions and cost estimates
  • Generate machine-readable recommendations that can be fed into automation pipelines for scheduled scaling

FAQ

What data do I need to provide for accurate analysis?

Provide historical metrics (CPU, memory, storage, network, request rates) with timestamps and any known traffic events; higher-resolution and longer history improve accuracy.

Can the skill recommend both vertical and horizontal scaling?

Yes. The skill evaluates trade-offs and recommends vertical resizing, horizontal scaling, sharding, or migrations based on observed patterns and cost implications.