Skill UI

Provides comprehensive strategies for minimizing API credit consumption when using SerpApi. Techniques include implementing aggressive caching with Redis, utilizing the free Archive API for historical data retrieval, and selecting the appropriate engine (like Google Light API) to balance cost and speed. Includes cost calculation models and usage monitoring scripts.

A comprehensive production readiness checklist for integrating SerpApi into live applications. This guide covers critical steps including secure API key management, setting up usage monitoring and credit budgets, implementing robust error handling, and optimizing performance for high availability. Use this when deploying or upgrading search features powered by SerpApi.

A comprehensive guide to managing API credit consumption and rate limits for SerpApi. This skill demonstrates how to implement robust throttling mechanisms using Python (Semaphore) and TypeScript (PQueue). It covers monitoring remaining account credits, slowing down requests to comply with per-second limits, and utilizing the search archive feature to optimize search volume and prevent unnecessary credit expenditure.

This guide outlines essential security best practices for managing and protecting your SerpApi API key. Since the key grants full account access, developers must never expose it in client-side code. It details how to implement secure backend proxies, manage environment variables using secret managers, set up rate limiting to prevent abuse, and monitor usage patterns in production environments.

This skill implements comprehensive SERP (Search Engine Results Page) monitoring using SerpApi. It covers asynchronous search result retrieval via polling and builds robust pipelines for tracking keyword rankings over time. Ideal for SEO tools, competitive intelligence, and automated performance monitoring.

This guide provides a comprehensive setup for Continuous Integration/Continuous Deployment (CI/CD) pipelines for Shopify apps. It utilizes GitHub Actions to automate linting, unit testing, and critical integration tests. Key features include API version compatibility checking, secure secret management, and streamlined deployment via the Shopify CLI, ensuring stable and reliable e-commerce functionality. Ideal for setting up automated release cycles or monitoring API changes.

Set up comprehensive observability for Shopify app integrations. This skill tracks crucial metrics like GraphQL query costs, REST rate limit consumption, webhook delivery success, and API latency. It is essential for production monitoring, setting up robust Prometheus metrics, and configuring alerts for performance bottlenecks in e-commerce SaaS environments.

This comprehensive benchmark suite evaluates the performance of Vision-Language Models (VLM) on complex video anomaly detection tasks using the SmartHome-Bench dataset. It covers a wide range of real-world smart home scenarios, including security breaches, elderly fall detection, and unusual pet behavior. Unlike single-frame analysis, this benchmark requires deep multi-frame video understanding, making it a robust tool for testing the advanced AI capabilities of video monitoring systems.

This skill provides comprehensive SQL queries and procedures to analyze and optimize Snowflake usage costs. It covers budgeting via resource monitors, right-sizing compute warehouses, tuning auto-suspend settings, and minimizing storage costs. Use it when reviewing billing, implementing cost controls, or reducing credit consumption in your Snowflake environment.

A comprehensive runbook for rapid incident response to Snowflake outages, query failures, and pipeline breaks. It guides users through systematic triage, checking account usage, managing resource monitors, and performing rollbacks using time travel, ensuring minimal data loss and quick recovery after critical data infrastructure incidents.

This guide provides a comprehensive method for setting up Snowflake observability. It teaches how to leverage built-in ACCOUNT_USAGE views to monitor critical metrics such as query performance (latency, error rates), credit consumption, and storage growth. Furthermore, it demonstrates how to implement automated alerts for operational issues (e.g., high failure rates, stuck warehouses) and export metrics to external monitoring systems like Grafana or Prometheus.

This comprehensive checklist guides the deployment of Snowflake data pipelines and integrations into a production environment. It covers critical areas such as authentication best practices, warehouse configuration, data pipeline readiness, access control, monitoring setup, and disaster recovery planning. Use it when preparing for a go-live or validating the stability of your production Snowflake setup.