cnoe-io/aws-cost-analysis
ui/src/skills/aws-cost-analysis/SKILL.md
Analyze AWS costs by service, account, and time period. Identifies top spenders, cost anomalies, and optimization opportunities. Use when reviewing cloud spend, preparing cost reports, or investigating unexpected charges.
$ install --global
skillsauthnpx skillsauth add cnoe-io/ai-platform-engineering aws-cost-analysisInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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SKILL.md
- name:
- aws-cost-analysis
- description:
- Analyze AWS costs by service, account, and time period. Identifies top spenders, cost anomalies, and optimization opportunities. Use when reviewing cloud spend, preparing cost reports, or investigating unexpected charges.
AWS Cost Analysis
Query AWS Cost Explorer data to break down spending by service, identify trends, detect anomalies, and recommend cost optimization actions.
Instructions
Phase 1: Cost Breakdown
- Fetch cost data using the AWS agent's Cost Explorer tools:
- Total spend for the requested period (default: last 30 days)
- Breakdown by AWS service (EC2, EKS, S3, RDS, Lambda, etc.)
- Breakdown by account (if multi-account)
- Daily/weekly cost trends
- Calculate key metrics:
- Month-over-month change (absolute and percentage)
- Top 5 most expensive services
- Top 5 fastest-growing services (by percentage increase)
Phase 2: Anomaly Detection
- Identify cost anomalies:
- Services with >20% cost increase vs. previous period
- Sudden spikes in daily spend
- New services that appeared this period
- Unused resources still incurring charges
- Flag potential waste:
- Idle EC2 instances (low CPU utilization)
- Unattached EBS volumes
- Old snapshots and AMIs
- Underutilized RDS instances
- NAT Gateway data transfer costs
Phase 3: Optimization Recommendations
Provide actionable recommendations with estimated savings:
- Reserved Instances or Savings Plans opportunities
- Right-sizing overprovisioned resources
- Storage tier optimization (S3 lifecycle policies)
- Spot Instance candidates for non-critical workloads
- Cleanup of orphaned resources
Output Format
## AWS Cost Analysis Report
**Period**: Feb 1 - Feb 9, 2026 | **Total Spend**: $24,567.89
### Cost Trend
| Week | Spend | Change |
|------|-------|--------|
| Jan 27 - Feb 2 | $5,890 | baseline |
| Feb 3 - Feb 9 | $6,234 | +5.8% |
### Top 5 Services by Cost
| Service | Cost | % of Total | MoM Change |
|---------|------|------------|------------|
| Amazon EKS | $8,234 | 33.5% | +12% |
| Amazon EC2 | $6,789 | 27.6% | -3% |
| Amazon S3 | $3,456 | 14.1% | +2% |
| Amazon RDS | $2,345 | 9.5% | +0% |
| AWS Lambda | $1,234 | 5.0% | +45% |
### Anomalies Detected
1. **Lambda costs up 45%** - New function `data-pipeline-processor` deployed Feb 3
2. **EKS costs up 12%** - Node group scaled from 5 to 8 nodes
### Optimization Opportunities
| Recommendation | Estimated Monthly Savings |
|---------------|--------------------------|
| Right-size 3 oversized EC2 instances | $450/mo |
| Purchase EKS Savings Plan | $1,200/mo |
| Delete 12 unattached EBS volumes | $180/mo |
| **Total Potential Savings** | **$1,830/mo** |
Examples
- "Show me the AWS cost breakdown for the last month"
- "What are our top 5 most expensive AWS services?"
- "Are there any cost anomalies this month?"
- "How can we reduce our AWS spend?"
- "Compare this month's AWS costs to last month"
Guidelines
- Default to last 30 days if no time period is specified
- Always show both absolute costs and percentage of total
- Include month-over-month comparison for context
- Round costs to 2 decimal places for totals, whole dollars for individual services
- When costs exceed expectations, investigate the root cause before recommending action
- Be specific in optimization recommendations (name the resource, not just the category)
- Distinguish between one-time spikes and sustained cost increases
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