Skill UI

A comprehensive, production-grade reference architecture for integrating with Apollo.io. It details a layered design encompassing API services, business logic, background job processing (e.g., lead enrichment), and data modeling, enabling the building of robust sales intelligence and CRM synchronization systems.

Automated assistant that walks through backend background worker setup, covering node.js, Python, Go, databases, caching, messaging, and microservices best practices.

A comprehensive guide to implementing reliable, scalable, and resilient background job processing in Node.js/TypeScript using BullMQ and Redis. Covers advanced patterns such as delayed jobs, repeatable scheduling, job dependencies (flows), rate limiting, robust error handling, and graceful worker shutdown, ensuring production-grade async execution.

This guide implements Deepgram's callback and webhook mechanism for handling asynchronous audio transcription. It provides a complete workflow, including submitting audio for background processing, setting up a secure webhook endpoint (with HMAC signature verification), and managing job status using Redis. Essential for integrating robust, delayed voice processing results into a production backend system.

Provides expert .NET/C# backend work for ASP.NET Core 8+ APIs, covering EF Core data access, authentication/authorization, background services, performance tuning, and production-ready patterns for enterprise services.

Build robust, event-driven integrations with Exa using scheduled monitoring and content alerts. This skill allows users to establish competitive intelligence pipelines, track content changes over time, and automate research digests. It supports new article detection, similarity monitoring, and reliable webhook delivery via background queues.

This guide demonstrates how to build a resilient, event-driven architecture for Gamma API integrations when native webhooks are unavailable. It utilizes a poll-based pattern, creating synthetic application-level events (start, completed, failed) by wrapping polling logic within an EventEmitter or message queue. Ideal for building background workers that reliably track and react to the full lifecycle of content generation.

Inngest integration for building durable, serverless-first background jobs and event-driven workflows. Use typed events, step functions, fan-out, retries, scheduling, and webhook handlers without managing queues or workers.

This skill provides a comprehensive pattern for building robust, scalable, and fault-tolerant asynchronous video generation pipelines using Kling AI. It implements advanced software engineering patterns, including Redis queues (Producer/Consumer), State Machines, and event-driven callbacks. It is designed for managing complex, multi-step AI workflows—such as generate, extend, and download—ensuring reliable background task processing.

A comprehensive guide to implementing advanced asynchronous patterns with Mistral AI. This skill covers using the Agents API for stateful, multi-turn workflows, the Batch API for cost-effective bulk inference, and event-driven streaming architectures. It is essential for building robust, long-running, or high-volume AI applications that require reliable background job handling.

Automates comprehensive monitoring and alerting of HTTP, database, API, background job, and client errors so teams can track, analyze, and resolve reliability issues before they impact users.

Guides orchestrating multiple Task tool subagents with run_in_background for concurrent work, covering when to trigger parallelism, how to craft prompts, launch in one message, synchronize results, and integrate TodoWrite status updates.