Skill UI

This skill provides comprehensive reference architectures for building production-grade AI applications using OpenRouter as a unified LLM gateway. It covers three scaling patterns: simple single-service, standard microservice (with caching and budget enforcement), and enterprise event-driven systems (with message queues and workers). Use this when planning system design, reviewing complex AI pipelines, or ensuring scalability and cost control in your LLM integration.

This skill enables the development of robust, event-driven pipelines interacting with the Perplexity Sonar API. Since Perplexity lacks native webhooks, this system simulates event patterns using advanced techniques: Streaming Server-Sent Events (SSE) for real-time data, job queues (like BullMQ/SQS) for asynchronous batch research, and cron-triggered monitoring for scheduled news and trend alerts. It provides patterns for building complex, reliable, and scalable AI applications.

Automated guidance for setting up RabbitMQ queues in backend services, covering patterns, code snippets, and validation for Node.js, Python, Go, and microservices messaging scenarios.

A comprehensive guide to implementing enterprise-grade Supabase architectures. This skill covers advanced patterns like monorepo layout, multi-tenant Row Level Security (RLS) isolation, microservices integration, and operational patterns (caching, queues, audit logging). Use this when building complex, scalable, and production-ready applications on Supabase.

Upstash QStash expert handles serverless message queues, scheduled HTTP jobs, retries, deduplication, and callback tracking so you can deliver asynchronous tasks without managing infrastructure.

A comprehensive guide for authorized penetration testers on identifying and exploiting insecure deserialization vulnerabilities across multiple languages (Java, PHP, Python, .NET). Covers techniques for generating payloads using tools like ysoserial and phpggc, and testing various application components such as cookies, HTTP parameters, and message queues to achieve potential Remote Code Execution (RCE).

This guide details the Hexagonal Architecture (Ports and Adapters) pattern, a robust method for decoupling core business logic from external infrastructure concerns. It teaches how to structure applications to make the domain model independent of databases, UI frameworks, or message queues. Implementing this pattern drastically improves testability, maintainability, and the ability to swap out external services without rewriting business rules.

This guide implements production-grade reliability patterns for integrating with external APIs, specifically Adobe services. It demonstrates how to use circuit breakers to prevent cascading failures, implement graceful degradation with cached fallbacks, and utilize dead letter queues (DLQ) for reliable asynchronous job handling. It ensures your application maintains high availability even when external services are unstable or rate-limited.

This guide details how to set up and test Apify Actors locally using the Apify CLI. It emulates the full platform environment (including datasets, key-value stores, and request queues), allowing developers to run scrapers, test data handling, and debug the entire development lifecycle before deploying to the cloud. Perfect for rapid iteration and rigorous local testing.

A robust reference architecture designed for integrating multi-property portfolios with the AppFolio Stack API. It manages complex tasks such as real-time vacancy tracking, tenant lifecycle management, work order routing, and financial accounting reconciliation (e.g., QuickBooks/Xero). Key components include a service layer, multi-level caching strategies for optimal data freshness, and an event-driven pipeline (using webhooks and message queues) to ensure data consistency and idempotency across all transactions, addressing potential rate limits and failure modes.

This guide documents the practical throughput limits and throttling patterns for automating Apple Notes operations (Create, Read, Search, Delete) via scripts like osascript. It provides technical solutions, including TypeScript throttling queues and Bash batch processing examples, to prevent common timeouts (-1712), sync lag, or data loss when performing high-volume, reliable automation on macOS.

This guide details advanced patterns for managing API rate limits, particularly for external AI services like Cohere. It covers implementing exponential backoff with jitter for handling transient 429 errors, utilizing concurrency-limited request queues, and building proactive rate limit trackers. These techniques ensure highly reliable and optimized API throughput in production systems.