snowflake-query-analyzer

Analyze Snowflake queries for performance bottlenecks and cost drivers.

Updated Aug 27, 2026

Search Tags:#performance #optimization #query #snowflake #cost #query-profile

Ready to run

npx skills add https://github.com/jwest33/claude_code_plugin_dbt_snowflake_specialist --skill snowflake-query-analyzer

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: snowflake-query-analyzer
Source: https://github.com/jwest33/claude_code_plugin_dbt_snowflake_specialist/tree/main/skills/snowflake-query-analyzer
Command: npx skills add https://github.com/jwest33/claude_code_plugin_dbt_snowflake_specialist --skill snowflake-query-analyzer

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires snowflake-connector-python, and includes scripts (resource) components.

What problem does it solve?

This Skill analyzes Snowflake query performance, identifies optimization opportunities, and provides cost reduction recommendations. It helps you reduce run times and compute costs while ensuring reliable results.

Core Features & Use Cases

Query Profile Analysis: Examine execution time, bytes scanned, pruning, and credits.
Optimization Strategies: Clustering keys, incremental processing, and caching.
Cost Analysis & Reporting: Compute potential cost savings and visualize improvements.

Quick Start

Run the analysis for a specific query using the included Python script, for example: python analyze_snowflake.py --query-id <QUERY_ID> or --model fct_orders to fetch related queries.

Frequently Asked Questions about snowflake-query-analyzer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I identify performance bottlenecks in my Snowflake queries?▼

Snowflake query performance analysis examines execution time, bytes scanned, partition pruning, and spilling to pinpoint bottlenecks. The Skill connects to INFORMATION_SCHEMA, computes execution metrics, and outputs structured JSON highlighting which query stages consume the most resources and credits.

What optimization strategies reduce Snowflake query costs?▼

Cost reduction strategies include clustering key design, incremental processing, and caching to minimize bytes scanned and warehouse compute time. The Skill analyzes query profiles to recommend which optimization applies to your workload and estimates potential cost savings.

Can I analyze multiple Snowflake queries at once or just individual queries?▼

The Skill analyzes individual queries by query ID and can fetch related queries using model parameters like `--model fct_orders`, enabling batch analysis across workloads. Results output as structured JSON for downstream cost analysis and reporting across multiple warehouses.

What Snowflake data do I need to provide before running query analysis?▼

Access to Snowflake INFORMATION_SCHEMA and query IDs or table names are prerequisites. The Skill requires snowflake-connector-python to authenticate and retrieve query execution history, metrics, and metadata needed for performance and cost analysis.

How do I export query optimization results for reporting or downstream tools?▼

Query analysis outputs structured JSON containing execution metrics, cost drivers, and optimization recommendations. This JSON format integrates with downstream reporting tools, dashboards, and cost visualization platforms for further analysis.

Does this work for troubleshooting high-cost workloads across multiple Snowflake warehouses?▼

Yes, the Skill detects partition pruning, spilling, and credit consumption across warehouse queries. It satisfies multi-warehouse performance troubleshooting by analyzing INFORMATION_SCHEMA data and providing cost-driver reports applicable to any warehouse configuration.