What problem does it solve? Designing asynchronous task infrastructure for backend systems is error-prone and time-consuming. This Skill automates the creation of a complete BullMQ queue architecture document (QUEUE_SPECS.md) from existing API specs, service designs, or business logic descriptions, ensuring consistent retry, timeout, and monitoring strategies. ## Core Features & Use Cases - Automatic Queue Identification: Scans business logic to detect time-consuming tasks (AI generation, file export, batch processing) and maps them to dedicated Queues, Jobs, and Workers. - Complete Reliability Design: Produces task state machines (PENDING/PROCESSING/COMPLETED/FAILED), retry policies with exponential backoff, timeout limits, and priority strategies. - AI Project Special Rules: Detects Novel/Script/Character/Scene entities and generates a tailored pipeline (generate-script → analyze-character → generate-scene → save-script). - Use Case: Given a SERVICE_SPECS.md describing generateScript() and exportPdf(), the Skill outputs a full QUEUE_SPECS.md with Job interfaces, Worker responsibilities, Redis key design, monitoring metrics, and risk analysis. ## Quick Start Ask the AI to generate a BullMQ queue design document from your SERVICE_SPECS.md or API_SPECS.md file.
