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snowflake-development

snowflake-development

github.com/borgheiData & databases1.0k67 installsUpdated 5d ago
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About snowflake-development

snowflake-development is a skill for data engineers working with Snowflake SQL and warehouse sizing. Its command-line helper analyzes or optimizes queries and recommends warehouse sizes based on workload type and data volume.

Key features

  1. 01Snowflake SQL analysis
  2. 02Query optimization suggestions
  3. 03Workload-based warehouse sizing
  4. 04Data-volume input for recommendations

Use cases

  1. 01Review a slow Snowflake SQL query
  2. 02Optimize a SQL file
  3. 03Estimate warehouse sizing for ETL or BI workloads

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/borghei/claude-skills --skill snowflake-development

After installing, type/snowflake-developmentin Claude Code to confirm it loaded.

Bundled filesreferences/snowflake-best-practices.mdscripts/snowflake_query_helper.py

Details

From the project README

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.

Clarify First

Before analyzing or sizing, settle the inputs below. When one is missing or vague and would change the result, ask about it; when it wouldn't, use a sensible default and say which one you used.

  • Action: analyze / optimize / warehouse-sizing (--action; selects the workflow).
  • SQL file or query: the specific query(ies) to optimize (--file; the subject of the analysis).
  • Workload type & data volume: ETL / BI / ad-hoc and the GB scale (--workload/--data-volume; drives the warehouse recommendation).

Ask about the two or three inputs that matter most for this request, not the whole list. If the user wants a result straight away, produce it and state your assumptions at the top.

Quick Start

# Analyze a Snowflake SQL file for optimization opportunities
python scripts/snowflake_query_helper.py --file queries.sql --action analyze

# Get warehouse sizing recommendations
python scripts/snowflake_query_helper.py --action warehouse-sizing --workload "etl" --data-volume "500GB"

# Optimize a specific query
python scripts/snowflake_query_helper.py --file slow_query.sql --action optimize

Tools Overview

ToolPurposeKey Flags
snowflake_query_helper.pyAnalyze, optimize Snowflake SQL and recommend warehouse sizes--file, --action, --workload, --data-volume

Workflows

Query Performance Optimization
  1. Collect slow queries from query history
  2. Run analyzer to identify optimization opportunities
  3. Apply recommended changes
  4. Compare before/after execution plans
Warehouse Right-Sizing
  1. Identify workload type (ETL, BI, ad-hoc, etc.)
  2. Run warehouse-sizing with data volume
  3. Review recommendations
  4. 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

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