generate_cost_report
Analyze AWS service costs by producing detailed reports that include unit pricing, calculation breakdowns, assumptions, and exclusions. Choose markdown or CSV.
Instructions
Generate a detailed cost analysis report based on pricing data for one or more AWS services.
This tool requires AWS pricing data and provides options for adding detailed cost information.
IMPORTANT REQUIREMENTS:
ALWAYS include detailed unit pricing information (e.g., "$0.0008 per 1K input tokens")
ALWAYS show calculation breakdowns (unit price × usage = total cost)
ALWAYS specify the pricing model (e.g., "ON DEMAND")
ALWAYS list all assumptions and exclusions explicitly
Output Format Options:
'markdown' (default): Generates a well-formatted markdown report
'csv': Generates a CSV format report with sections for service information, unit pricing, cost calculations, etc.
Example usage:
{
// Required parameters
"pricing_data": {
// This should contain pricing data retrieved from get_pricing
"status": "success",
"service_name": "bedrock",
"data": "... pricing information ...",
"message": "Retrieved pricing for bedrock from AWS Pricing url"
},
"service_name": "Amazon Bedrock",
// Core parameters (commonly used)
"related_services": ["Lambda", "S3"],
"pricing_model": "ON DEMAND",
"assumptions": [
"Standard ON DEMAND pricing model",
"No caching or optimization applied",
"Average request size of 4KB"
],
"exclusions": [
"Data transfer costs between regions",
"Custom model training costs",
"Development and maintenance costs"
],
"output_file": "cost_analysis_report.md", // or "cost_analysis_report.csv" for CSV format
"format": "markdown", // or "csv" for CSV format
// Advanced parameter for complex scenarios
"detailed_cost_data": {
"services": {
"Amazon Bedrock Foundation Models": {
"usage": "Processing 1M input tokens and 500K output tokens with Claude 3.5 Haiku",
"estimated_cost": "$80.00",
"free_tier_info": "No free tier for Bedrock foundation models",
"unit_pricing": {
"input_tokens": "$0.0008 per 1K tokens",
"output_tokens": "$0.0016 per 1K tokens"
},
"usage_quantities": {
"input_tokens": "1,000,000 tokens",
"output_tokens": "500,000 tokens"
},
"calculation_details": "$0.0008/1K × 1,000K input tokens + $0.0016/1K × 500K output tokens = $80.00"
},
"AWS Lambda": {
"usage": "6,000 requests per month with 512 MB memory",
"estimated_cost": "$0.38",
"free_tier_info": "First 12 months: 1M requests/month free",
"unit_pricing": {
"requests": "$0.20 per 1M requests",
"compute": "$0.0000166667 per GB-second"
},
"usage_quantities": {
"requests": "6,000 requests",
"compute": "6,000 requests × 1s × 0.5GB = 3,000 GB-seconds"
},
"calculation_details": "$0.20/1M × 0.006M requests + $0.0000166667 × 3,000 GB-seconds = $0.38"
}
}
},
// Recommendations parameter - can be provided directly or generated
"recommendations": {
"immediate": [
"Optimize prompt engineering to reduce token usage for Claude 3.5 Haiku",
"Configure Knowledge Base OCUs based on actual query patterns",
"Implement response caching for common queries to reduce token usage"
],
"best_practices": [
"Monitor OCU utilization metrics and adjust capacity as needed",
"Use prompt caching for repeated context across API calls",
"Consider provisioned throughput for predictable workloads"
]
}
}Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| format | No | Output format ("markdown" or "csv") | markdown |
| exclusions | No | List of items excluded from cost analysis | |
| assumptions | No | List of assumptions for cost analysis | |
| output_file | No | Path to save the report file | |
| pricing_data | Yes | Raw pricing data from AWS pricing tools | |
| service_name | Yes | Name of the AWS service | |
| pricing_model | No | Pricing model (e.g., "ON DEMAND", "Reserved") | ON DEMAND |
| recommendations | No | Direct recommendations or guidance for generation | |
| related_services | No | List of related AWS services | |
| detailed_cost_data | No | Detailed cost information for complex scenarios |
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |