Skill UI

This guide provides a minimal, working example of connecting to a Shopify store using the GraphQL Admin API. It demonstrates how to initialize the API client, authenticate the connection, and execute a query to retrieve product and variant details. Ideal for developers starting a new e-commerce integration, testing API connectivity, or learning basic Shopify data retrieval patterns.

A comprehensive guide for rapid incident response when Shopify integrations fail or behave unexpectedly. It instructs users to triage issues by checking the status page, diagnosing API connectivity, and handling common errors like rate limits (429) or expired tokens (401). Includes decision trees, immediate mitigation steps, and communication templates.

This guide details how to implement robust and secure authentication for Shopify applications using the official @shopify/shopify-api SDK. It covers three main authentication methods: OAuth flow for public apps, session token exchange for embedded apps, and private access for custom apps. Use this skill when setting up, connecting, or debugging any application that requires deep integration and secure API access to Shopify's admin or storefront data.

This guide provides a comprehensive framework for load testing Shopify app integrations, specifically designed to respect strict API rate limits. It teaches users how to plan and benchmark system capacity for high-traffic events like Black Friday/Cyber Monday (BFCM) or flash sales using tools like k6. Users learn to optimize for burst events, analyze GraphQL cost, and configure infrastructure scaling for reliable e-commerce performance.

This guide provides a comprehensive and reproducible local development workflow for Shopify applications. It details how to use the Shopify CLI for scaffolding and hot reloading, integrate ngrok for stable webhook tunneling, and set up Vitest for robust API testing, enabling developers to achieve rapid and reliable iteration cycles.

Implement comprehensive automated policy enforcement for Shopify apps, ensuring security and adherence to App Store guidelines. This skill includes ESLint rules for detecting hardcoded API secrets, enforcing GraphQL query cost budgets, and running pre-commit hooks and CI checks for critical compliance validations (e.g., GDPR webhooks). Use it when hardening a production-ready Shopify application.

A comprehensive quick reference guide for diagnosing and resolving common operational and compilation errors encountered when working with Snowflake. It provides actionable solutions for issues like 'Object Does Not Exist', connectivity failures, authentication problems, and SQL syntax mistakes across various programming languages and drivers (Python, Node.js).

Collects comprehensive diagnostic evidence from Snowflake's ACCOUNT_USAGE views, QUERY_HISTORY, and environment details. This tool is essential for troubleshooting persistent performance issues, connection failures, or preparing detailed support cases for Snowflake support, ensuring all necessary logs, query metrics, and resource usage data are collected in one package.

Master the deployment of applications connected to Snowflake across various cloud environments, including serverless functions (AWS Lambda, Cloud Run) and containers. This guide covers best practices for secure connection management, connection pooling, handling secrets (like private keys), and ensuring application reliability in production settings.

This guide provides minimal working examples for connecting to Snowflake and executing core SQL operations. It comprehensively covers connection setup, running simple SELECT queries, creating databases and tables, and performing parameterized inserts using both Python and Node.js. It is ideal for initial environment setup, testing the Snowflake SDK, or learning fundamental data warehouse interactions.

This guide provides comprehensive steps to install and configure Snowflake SDKs for Node.js and Python. It covers various authentication methods, including password, secure Key Pair authentication (ideal for CI/CD), and enterprise-grade SSO/OAuth integration. Use this when setting up data pipelines or applications that require reliable and secure connectivity to the Snowflake data warehouse.

This guide provides a comprehensive methodology for load testing and capacity planning within Snowflake data warehouses. It covers optimizing query performance by adjusting warehouse sizes (Scale UP), simulating high concurrency using multi-threading (Scale OUT), and configuring advanced scaling policies (Standard, Economy, Maximized). Users can benchmark critical queries using SQL and simulate real-world user traffic using Python, ensuring robust and cost-efficient production environments.