Snowflake Development
Covers writing Snowflake SQL, building pipelines with Dynamic Tables or Streams and Tasks, Cortex AI functions, and Snowpark Python.
Before & after
Same prompt, same agent — the only difference is the skill.
I can help you write SQL for Snowflake. Dynamic Tables are a good approach for aggregating metrics because they refresh automatically based on the underlying data. You'll want to think about your fact table structure, what dimensions you need to aggregate across, and how often you want the refresh to happen. Snowflake also has stream and task features if you want more control. What's the source of your hourly data—is it coming from an event stream or a batch load?
DYNAMIC TABLE SCRIPT TABLE: agg_sales_metrics_hourly (auto-refresh) SOURCE CONFIGURATION Base table: raw_sales_events Granularity: hourly (refresh lag: 5 minutes) Target warehouse: analytics_wh (auto-suspend after 2 min idle) SCRIPT STRUCTURE Step 1 → Parse event timestamp to hour bucket Step 2 → Group by: region, product_category, customer_segment, hour Step 3 → Calculate: transaction_count, revenue_sum, avg_order_value, unique_customers Step 4 → Apply data quality filters (remove negative revenue, null region) Step 5 → Sort by hour DESC, region ASC for query performance RESULTING COLUMNS • hour_utc (timestamp) • region (string) • product_category (string) • customer_segment (string) • transaction_count (number) • revenue_sum (decimal) • avg_order_value (decimal) • unique_customers (number) • refresh_time (timestamp) PERFORMANCE TUNING Cluster key: hour_utc, region (reduces scan time for hourly reports) Stream attached: captures incremental updates to source table MONITORING Check query history if refresh times exceed 10 minutes
About this skill
name: snowflake-development description: Use when Use when writing Snowflake SQL, building data pipelines with Dynamic Tables or Streams/Tasks, using Cortex AI functions, creating Cortex Agents, writing Snowpark Python, configuring dbt for Snowfla...
Snowflake Development
Use when writing Snowflake SQL, building data pipelines with Dynamic Tables or Streams/Tasks, using Cortex AI functions, creating Cortex Agents, writing Snowpark Python, configuring dbt for Snowflake, or troubleshooting Snowflake errors.
What you get
- Public GitHub repo (alirezarezvani/claude-skills)
- the snowflake-development skill folder with SKILL.md. Part of a 337-skill / 30-agent / 70-command install.
Customize your output
- Fork the repo and adapt the skill's instructions and references to your workflow.
Example output
Activates automatically when your request matches Snowflake Development; chains with the other skills, agents, and commands in the collection.
Best for
Creators, builders, and teams using Claude Code.
SKILL.md preview
---
name: snowflake-development
description: Use this skill when writing Snowflake SQL, building pipelines with Dynamic Tables or Streams and Tasks, using Cortex AI functions, or writing Snowpark Python.
version: 1.0.0
category: Development / Engineering
author: AgentVolt
license: proprietary
tags:
- development
- engineering
---
# Snowflake Development
Covers writing Snowflake SQL, building pipelines with Dynamic Tables or Streams and Tasks, Cortex AI functions, and Snowpark Python.
## When to use
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