Cost Optimizer (Cloud Data Platforms)
Analyzes and optimizes costs for cloud data platforms
Best use case
Cost Optimizer (Cloud Data Platforms) is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Analyzes and optimizes costs for cloud data platforms
Teams using Cost Optimizer (Cloud Data Platforms) should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/cost-optimizer/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How Cost Optimizer (Cloud Data Platforms) Compares
| Feature / Agent | Cost Optimizer (Cloud Data Platforms) | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Analyzes and optimizes costs for cloud data platforms
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Cost Optimizer (Cloud Data Platforms)
## Overview
Analyzes and optimizes costs for cloud data platforms. This skill provides deep expertise in platform-specific cost structures and optimization strategies.
## Capabilities
- Snowflake credit analysis and optimization
- BigQuery slot and on-demand optimization
- Redshift node sizing
- Storage cost optimization
- Query cost estimation
- Warehouse scheduling recommendations
- Data lifecycle policy recommendations
- Reserved capacity planning
## Input Schema
```json
{
"platform": "snowflake|bigquery|redshift|databricks",
"usageMetrics": "object",
"billingData": "object",
"queryHistory": "object"
}
```
## Output Schema
```json
{
"currentCost": "number",
"optimizedCost": "number",
"savings": "percentage",
"recommendations": [{
"category": "string",
"action": "string",
"impact": "number",
"effort": "low|medium|high"
}]
}
```
## Target Processes
- Data Warehouse Setup
- Query Optimization
- Pipeline Migration
## Usage Guidelines
1. Provide platform-specific usage metrics
2. Include billing data for cost baseline
3. Share query history for optimization analysis
4. Prioritize recommendations by impact and effort
## Best Practices
- Regularly review and optimize warehouse sizes
- Implement auto-suspend and auto-resume policies
- Use clustering and partitioning to reduce scan costs
- Consider reserved capacity for predictable workloads
- Monitor and alert on cost anomaliesRelated Skills
structured-data
JSON-LD schema markup and validation.
svg-optimizer
Optimize SVG assets, generate sprites, and convert to React components
cloudformation-analyzer
Validate and analyze AWS CloudFormation templates for security and best practices
CVE/CWE Database Skill
CVE and CWE database querying and management
cloud-security-testing
Multi-cloud security assessment and penetration testing capabilities. Execute Prowler/ScoutSuite assessments, analyze IAM policies, identify cloud misconfigurations, test permissions, and enumerate cloud resources across AWS/GCP/Azure.
multi-cloud-security-posture
Unified cloud security posture management across AWS, Azure, and GCP with normalized metrics and CIS benchmark comparison
Point Cloud Processing Skill
Specialized skill for 3D point cloud processing and analysis using PCL and Open3D
test-data-generation
Synthetic test data generation and management using Faker.js and similar tools. Generate realistic test data, create data factories, implement database seeding, and manage test data anonymization.
iOS Persistence (Core Data/Realm)
Specialized skill for iOS local data persistence solutions
Room Database
Expert skill for Android Room persistence library
metadata-standards-implementation
Apply Dublin Core, METS, MODS, and other metadata schemas for digital collections and archival materials
health-data-integration
Facilitate interoperability between health IT systems including EHR, HIE, and clinical decision support through HL7, FHIR, and other healthcare data standards