cost-optimization
Helps your agent optimize cloud costs through spending analysis and resource rightsizing.
What it does
This tool helps reduce costs for cloud services (like AWS, Azure, GCP). It suggests how to use resources better, identify unused items, and apply savings strategies.
When to use it
- ✓When cloud spending is too high.
- ✓To find and remove unused resources.
- ✓To plan future cloud expenses.
Example of what to ask your AI
“How can I reduce my AWS costs?”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
The tool analyzes your cloud resource usage, like virtual machines and storage. It suggests adjustments, such as downsizing oversized resources or using cheaper options for specific workloads.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add wshobson/agents --skill cost-optimizationOr download just the file:
curl -L https://raw.githubusercontent.com/wshobson/agents/main/plugins/cloud-infrastructure/skills/cost-optimization/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
Cloud Cost Optimization
Strategies and patterns for optimizing cloud costs across AWS, Azure, GCP, and OCI.
Purpose
Implement systematic cost optimization strategies to reduce cloud spending while maintaining performance and reliability.
When to Use
- Reduce cloud spending
- Right-size resources
- Implement cost governance
- Optimize multi-cloud costs
- Meet budget constraints
Cost Optimization Framework
1. Visibility
- Implement cost allocation tags
- Use cloud cost management tools
- Set up budget alerts
- Create cost dashboards
2. Right-Sizing
- Analyze resource utilization
- Downsize over-provisioned resources
- Use auto-scaling
- Remove idle resources
3. Pricing Models
- Use reserved capacity
- Leverage spot/preemptible instances
- Implement savings plans
- Use committed use discounts
4. Architecture Optimization
- Use managed services
- Implement caching
- Optimize data transfer
- Use lifecycle policies
AWS Cost Optimization
Reserved Instances
Savings: 30-72% vs On-Demand
Term: 1 or 3 years
Payment: All/Partial/No upfront
Flexibility: Standard or Convertible
Savings Plans
Compute Savings Plans: 66% savings
EC2 Instance Savings Plans: 72% savings
Applies to: EC2, Fargate, Lambda
Flexible across: Instance families, regions, OS
Spot Instances
Savings: Up to 90% vs On-Demand
Best for: Batch jobs, CI/CD, stateless workloads
Risk: 2-minute interruption notice
Strategy: Mix with On-Demand for resilience
S3 Cost Optimization
resource "aws_s3_bucket_lifecycle_configuration" "example" {
bucket = aws_s3_bucket.example.id
rule {
id = "transition-to-ia"
status = "Enabled"
transition {
days = 30
storage_class = "STANDARD_IA"
}
transition {
days = 90
storage_class = "GLACIER"
}
expiration {
days = 365
}
}
}
Azure Cost Optimization
Reserved VM Instances
- 1 or 3 year terms
- Up to 72% savings
- Flexible sizing
- Exchangeable
Azure Hybrid Benefit
- Use existing Windows Server licenses
- Up to 80% savings with RI
- Available for Windows and SQL Server
Azure Advisor Recommendations
- Right-size VMs
- Delete unused resources
- Use reserved capacity
- Optimize storage
GCP Cost Optimization
Committed Use Discounts
- 1 or 3 year commitment
- Up to 57% savings
- Applies to vCPUs and memory
- Resource-based or spend-based
Sustained Use Discounts
- Automatic discounts
- Up to 30% for running instances
- No commitment required
- Applies to Compute Engine, GKE
Preemptible VMs
- Up to 80% savings
- 24-hour maximum runtime
- Best for batch workloads
OCI Cost Optimization
Flexible Shapes
- Scale OCPUs and memory independently
- Match instance sizing to workload demand
- Reduce wasted capacity from fixed VM shapes
Commitments and Budgets
- Use annual commitments for predictable spend
- Set compartment-level budgets with alerts
- Track monthly forecasts with OCI Cost Analysis
Preemptible Capacity
- Use preemptible instances for batch and ephemeral workloads
- Keep interruption-tolerant autoscaling groups
- Mix with standard capacity for critical services
Tagging Strategy
AWS Tagging
locals {
common_tags = {
Environment = "production"
Project = "my-project"
CostCenter = "engineering"
Owner = "team@example.com"
ManagedBy = "terraform"
}
}
resource "aws_instance" "example" {
ami = "ami-12345678"
instance_type = "t3.medium"
tags = merge(
local.common_tags,
{
Name = "web-server"
}
)
}
Reference: See references/tagging-standards.md
Cost Monitoring
Budget Alerts
# AWS Budget
resource "aws_budgets_budget" "monthly" {
name = "monthly-budget"
budget_type = "COST"
limit_amount = "1000"
limit_unit = "USD"
time_period_start = "2024-01-01_00:00"
time_unit = "MONTHLY"
notification {
comparison_operator = "GREATER_THAN"
threshold = 80
threshold_type = "PERCENTAGE"
notification_type = "ACTUAL"
subscriber_email_addresses = ["team@example.com"]
}
}
Cost Anomaly Detection
- AWS Cost Anomaly Detection
- Azure Cost Management alerts
- GCP Budget alerts
- OCI Budgets and Cost Analysis
Architecture Patterns
Pattern 1: Serverless First
…
FAQ
What does 'right-sizing' mean?
'Right-sizing' means adjusting the size of resources (like virtual computers) so they use only what they truly need, avoiding waste.
What are 'reserved instances' or 'savings plans'?
These are long-term commitments (1 or 3 years) with the cloud provider that offer significant discounts compared to paying for usage on a moment-by-moment basis.
How does the tool help with unused resources?
It identifies and suggests removing resources that are attached but not being used, such as unallocated virtual disks or IP addresses.
Details
Original description by the author
Optimize cloud costs across AWS, Azure, GCP, and OCI through resource rightsizing, tagging strategies, reserved instances, and spending analysis. Use when reducing cloud expenses, analyzing infrastructure costs, or implementing cost governance policies.
repo: wshobson/agents
Popularity
- GitHub stars
- 41k
- Ranking position
- #4824
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
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