aws-cost-explorer

Name: aws-cost-explorer
Author: oldwinter

github.com/oldwinterCloud & DevOps1044 installsUpdated 1w ago

About aws-cost-explorer

A skill for querying AWS cost and usage data, suited to operators reviewing cloud spend. It supports service summaries and usage-type drill-downs with date, cost, and output controls.

Key features

01Daily costs by AWS service
02Usage-type breakdowns
03Date and minimum-cost filters
04Table or JSON output

Use cases

01Review daily spend across services
02Investigate a service’s usage charges
03Show only costs above a threshold

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/oldwinter/skills --skill aws-cost-explorer

After installing, type/aws-cost-explorerin Claude Code to confirm it loaded.

Bundled filesscripts/cost_query.py

Details

From the project README

AWS Cost Explorer

Query AWS costs and usage details with flexible granularity - from service-level overview to detailed usage type breakdown.

Capabilities

Query daily AWS costs by service (e.g., EC2, S3, OpenSearch, DocumentDB)
Drill down to usage type details for specific services (e.g., instance types, storage, data transfer)
Filter results by minimum cost threshold
Support both relative dates (days ago) and absolute dates (YYYY-MM-DD)
Output in human-readable table or JSON format

Usage

Quick Commands

To query costs, use the bundled script at scripts/cost_query.py:

# Query costs from 2 days ago (default) by service
python3 <skill-path>/scripts/cost_query.py

# Query yesterday's costs, show items > $5
python3 <skill-path>/scripts/cost_query.py --days-ago 1 --min-cost 5

# Query specific date
python3 <skill-path>/scripts/cost_query.py --date 2026-01-15

# Query specific service's usage breakdown
python3 <skill-path>/scripts/cost_query.py --service "Amazon OpenSearch Service" --min-cost 1

# Query all services with usage type details
python3 <skill-path>/scripts/cost_query.py --detailed --min-cost 5

# Output as JSON
python3 <skill-path>/scripts/cost_query.py --json --min-cost 5

Script Options

Option	Short	Description
`--days-ago`	`-d`	Query N days ago (default: 2, i.e., day before yesterday)
`--date`		Query specific date (YYYY-MM-DD format)
`--min-cost`	`-m`	Minimum cost threshold to display (default: 0)
`--service`	`-s`	Query usage type breakdown for a specific service
`--detailed`		Show all services with usage type breakdown
`--json`	`-j`	Output in JSON format

Common Service Names

When using --service, use the exact AWS service names:

Common Name	AWS Service Name
OpenSearch	`Amazon OpenSearch Service`
DocumentDB/MongoDB	`Amazon DocumentDB (with MongoDB compatibility)`
EC2 Compute	`Amazon Elastic Compute Cloud - Compute`
EC2 Other (EBS, NAT)	`EC2 - Other`
EFS	`Amazon Elastic File System`
S3	`Amazon Simple Storage Service`
RDS	`Amazon Relational Database Service`
EKS	`Amazon Elastic Container Service for Kubernetes`
VPC	`Amazon Virtual Private Cloud`
Bedrock	`Amazon Bedrock`
Lambda	`AWS Lambda`
CloudWatch	`AmazonCloudWatch`

Understanding Usage Types

Common usage type patterns:

Pattern	Meaning
`BoxUsage:*`	EC2 instance hours (e.g., `BoxUsage:m7i.large`)
`ESInstance:*`	OpenSearch instance hours
`EBS:VolumeUsage.*`	EBS storage (e.g., `EBS:VolumeUsage.gp3`)
`TimedStorage-ByteHrs`	S3/EFS storage capacity
`DataTransfer-*`	Data transfer costs
`NatGateway-*`	NAT Gateway costs
`VpcEndpoint-*`	VPC Endpoint costs
`-input-tokens` / `-output-tokens`	Bedrock token usage
`Elastic*Usage`	DocumentDB Elastic costs

Prerequisites

AWS CLI configured with appropriate credentials
IAM permissions for ce:GetCostAndUsage

Example Workflow

First, get service-level overview:

python3 <skill-path>/scripts/cost_query.py --min-cost 5

Identify high-cost services, then drill down:

python3 <skill-path>/scripts/cost_query.py --service "Amazon OpenSearch Service" --min-cost 1

For comprehensive analysis, use detailed mode:

python3 <skill-path>/scripts/cost_query.py --detailed --min-cost 5

Comments

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Details

Author: oldwinter
Repository: oldwinter/skills
Category: Cloud & DevOps
Installs: 44
GitHub stars: 10

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