What AWS permissions are required to use this skill?

You need the `ce:GetCostAndUsage` IAM permission to allow the tool to query the AWS Cost Explorer API for billing data.

Does the tool provide real-time Bedrock spending data?

No, the tool relies on AWS Cost Explorer, which typically has a 24-hour data processing delay.

Can I see a breakdown of costs by specific AWS regions?

Yes, by using the `--detail full` flag, the tool provides a regional breakdown of costs alongside model-specific data.

Do I need to install gnuplot for this skill to work?

Gnuplot is only required if you want to generate visual ASCII charts. The JSON and table outputs work without it.

AWS Bedrock Cost Analyzer

Name: AWS Bedrock Cost Analyzer
Author: dnvriend

bydnvriend

Cloud Infrastructure

Analyzes and visualizes AWS Bedrock model consumption and spending patterns directly from the CLI.

About

A professional CLI utility designed for developers and DevOps engineers to gain granular visibility into AWS Bedrock expenditures. It queries the AWS Cost Explorer API to provide detailed breakdowns of token usage—including input, output, and cache reads/writes—across different regions and models. By providing visual ASCII charts, formatted tables, and programmatic JSON output, it enables teams to identify cost spikes, optimize token consumption, and integrate cost reporting into automated workflows.

Key Features

0 GitHub stars
Granular token usage tracking for Input, Output, and Cache Write/Read operations
Multi-format output support including JSON, summary tables, and regional breakdowns
Flexible historical analysis with customizable periods from 1 day up to 1 year
Interactive visual reporting with ASCII line and bar charts using gnuplot
Programmatic Python API for custom cost-tracking integrations and automation

Use Cases

Generating automated weekly executive summaries of AI infrastructure spending
Identifying cost-heavy models or regions to drive budget optimization strategies
Integrating programmatic cost data into CI/CD pipelines to monitor AI deployment impact

About

Key Features

0 GitHub stars
Granular token usage tracking for Input, Output, and Cache Write/Read operations
Multi-format output support including JSON, summary tables, and regional breakdowns
Flexible historical analysis with customizable periods from 1 day up to 1 year
Interactive visual reporting with ASCII line and bar charts using gnuplot
Programmatic Python API for custom cost-tracking integrations and automation

Use Cases

Generating automated weekly executive summaries of AI infrastructure spending
Identifying cost-heavy models or regions to drive budget optimization strategies
Integrating programmatic cost data into CI/CD pipelines to monitor AI deployment impact