| name | snowflake-development |
| description | This skill should be used when the user asks to "optimize Snowflake queries", "analyze Snowflake SQL performance", "size Snowflake warehouses", "review Snowflake data models", or "troubleshoot Snowflake cost issues".
|
| license | MIT + Commons Clause |
| metadata | {"version":"1.0.0","author":"borghei","category":"engineering","domain":"data-warehouse","updated":"2026-04-02T00:00:00.000Z","tags":["snowflake","sql","data-warehouse","query-optimization","warehouse-sizing"]} |
Snowflake Development
Category: Engineering
Domain: Data Warehouse
Overview
The Snowflake Development skill provides tools for analyzing and optimizing Snowflake SQL queries, recommending warehouse sizing, and enforcing Snowflake-specific best practices. Helps data engineers reduce costs and improve query performance.
Quick Start
python scripts/snowflake_query_helper.py --file queries.sql --action analyze
python scripts/snowflake_query_helper.py --action warehouse-sizing --workload "etl" --data-volume "500GB"
python scripts/snowflake_query_helper.py --file slow_query.sql --action optimize
Tools Overview
| Tool | Purpose | Key Flags |
|---|
snowflake_query_helper.py | Analyze, optimize Snowflake SQL and recommend warehouse sizes | --file, --action, --workload, --data-volume |
Workflows
Query Performance Optimization
- Collect slow queries from query history
- Run analyzer to identify optimization opportunities
- Apply recommended changes
- Compare before/after execution plans
Warehouse Right-Sizing
- Identify workload type (ETL, BI, ad-hoc, etc.)
- Run warehouse-sizing with data volume
- Review recommendations
- Implement multi-cluster settings if applicable
Reference Documentation
Common Patterns
Cost Reduction
- Right-size warehouses (don't use XL for small queries)
- Set auto-suspend to 60 seconds for ad-hoc warehouses
- Use materialized views for frequently accessed aggregations
- Partition large tables with clustering keys
- Avoid SELECT * in production queries