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Async communication patterns using message brokers and task queues. Use when building event-driven systems, background job processing, or service decoupling. Covers Kafka (event streaming), RabbitMQ (complex routing), NATS (cloud-native), Redis Streams, Celery (Python), BullMQ (TypeScript), Temporal (workflows), and event sourcing patterns.
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Provides AWS messaging patterns using AWS SDK for Java 2.x for SQS queues and SNS topics. Handles sending/receiving messages, FIFO queues, DLQ, subscriptions, and pub/sub patterns. Use when implementing messaging with SQS or SNS.
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This skill should be used when the user asks to "set up Cloudflare Queues", "create a message queue", "implement queue consumer", "process background jobs", "configure queue retry logic", "publish messages to queue", "implement dead letter queue", or encountering "queue timeout", "message retry", "throughput exceeded", "queue backlog" errors.
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You are an expert in amqplib, the Node.js client for RabbitMQ and AMQP 0-9-1 protocol. You help developers implement reliable message queuing with work queues, pub/sub fanout, topic routing, RPC patterns, dead letter queues, and message acknowledgment — building decoupled microservices that communicate asynchronously through RabbitMQ.
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Use when an "enable observability" card asks for queues, or a worker's queue.backlog / consumer lag signals are unbound - which exporter or direct broker data source reads Kafka, RabbitMQ, NATS and Redis queues, the metric names the recipes expect, and the consumer-side metrics the developer adds
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Unified expert guide for async job queues & durable workflows: BullMQ v5 (Redis queues), Trigger.dev v3 (serverless tasks), Inngest, and Temporal.io (distributed sagas) / Panduan ahli terpadu untuk antrean job asinkron & workflow tahan-gagal: BullMQ v5, Trigger.dev v3, Inngest, dan Temporal.io.
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Cloudflare platform management via Wrangler CLI, Agents SDK (v0.13+), and Browser Rendering API. Deploy Pages, Workers, KV, R2, D1, Queues, Vectorize, Workflows, Hyperdrive. Build stateful AI agents with the full SDK stack — Agent, AIChatAgent, Think, Voice, sub-agents, fibers, HITL, scheduling, observability, Code Mode (Dynamic Worker sandboxes). Budget web scraping via cf_browser.py. Use when deploying to Cloudflare, managing CF infrastructure, configuring wrangler.toml/wrangler.jsonc, building AI agents or chat agents on Workers, adding voice, orchestrating sub-agents, or for cheap web scraping. Triggers: Cloudflare, wrangler, Pages, KV, R2, D1, Workers, Vectorize, Queues, Workflows, Hyperdrive, cf_browser, Browser Rendering, Agents SDK, Code Mode, codemode, MCP, Think, AIChatAgent, Voice agent, sub-agents, fibers, HITL, Dynamic Workers.
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Runs batch and HPC workloads on GKE, utilizing job queues and parallel processing. Use when running GKE batch jobs, configuring GKE HPC, or setting up GKE job queues. Don't use for standard web application deployments (use gke-app-onboarding instead).
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Configuring Salesforce lead management and conversion in Setup: lead settings, web-to-lead, conversion field mapping, lead queues, auto-response rules, lead processes. Trigger keywords: web-to-lead, lead conversion, lead field mapping, lead settings, lead process, lead queue, lead auto-response. NOT for Apex that controls what conversion creates - use apex/lead-conversion-customization. NOT for lead assignment rule logic - use admin/assignment-rules. NOT for duplicate rule configuration - use admin/duplicate-management. Also covers: LeadConvertSettings objectMapping XML, LeadConfigSettings, LeadStatus StandardValueSet converted flag, lead process BusinessProcess, Database.convertLead bulk conversion limits.
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Use when designing a background-job system, choosing between BullMQ / Sidekiq / RQ / Temporal / SQS, deciding queue-vs-workflow, sizing concurrency vs rate limits, building dead-letter queues, or making handlers idempotent. Triggers: jobs running twice on retry, lost jobs after worker crash, DLQ filling up, Redis OOM from job backlog, exactly-once requested, "do we need Temporal?", visibility timeout / lockDuration confusion, exponential backoff vs jitter, fan-out fan-in workflows. NOT for outbound webhook publishing (different concerns), receiver-side webhook handling (different concerns), event-streaming/Kafka topology, or in-process async (event loop only).
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Expert in background job processing with Bull/BullMQ (Redis), Celery, and cloud queues. Implements retries, scheduling, priority queues, and worker management. Use for async task processing, email campaigns, report generation, batch operations. Activate on "background job", "async task", "queue", "worker", "BullMQ", "Celery". NOT for real-time WebSocket communication, synchronous API calls, or simple setTimeout operations.
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Auto-activate for litestar_saq, SAQPlugin, SAQConfig, QueueConfig, TaskQueues, CronJob, litestar workers run, background jobs, schedules, or SAQ UI. Not for litestar-queues, Celery, RQ, or Dramatiq.
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Cloudflare Workers CLIでWorkers、KV、R2、D1、Vectorize、Hyperdrive、Workers AI、Containers、Queues、Workflows、Pipelines、Secrets Storeを開発・デプロイ・管理する。Wranglerコマンドを実行する前に使用し、最新の公式ドキュメントに基づく構文と安全規則を確認する。
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Use when designing a background-job system, choosing between BullMQ / Sidekiq / RQ / Temporal / SQS, deciding queue-vs-workflow, sizing concurrency vs rate limits, building dead-letter queues, or making handlers idempotent. Triggers: jobs running twice on retry, lost jobs after worker crash, DLQ filling up, Redis OOM from job backlog, exactly-once requested, "do we need Temporal?", visibility timeout / lockDuration confusion, exponential backoff vs jitter, fan-out fan-in workflows. NOT for outbound webhook publishing (different concerns), receiver-side webhook handling (different concerns), event-streaming/Kafka topology, or in-process async (event loop only).
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Expert in background job processing with Bull/BullMQ (Redis), Celery, and cloud queues. Implements retries, scheduling, priority queues, and worker management. Use for async task processing, email campaigns, report generation, batch operations. Activate on "background job", "async task", "queue", "worker", "BullMQ", "Celery". NOT for real-time WebSocket communication, synchronous API calls, or simple setTimeout operations.
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将大型功能的RFC设计提案拆分为带依赖关系和验收测试的工作单元，组织多个智能体完成调查、实现、测试与审查，再依次合并变更并验证整个系统。
在合并或部署Laravel项目前，依次检查环境、代码、测试覆盖率、依赖漏洞、数据库变更、缓存、队列及定时任务；前置检查失败时停止后续操作。
从测试开始实现 Laravel 功能，使用 PHPUnit 或 Pest 验证模型、API、身份认证和权限，模拟外部服务，并通过覆盖率了解测试执行了哪些代码。
在Claude Code中组合记忆、定时执行与任务队列，设计持续开展的工作流程，并指导配置外部运行环境及浏览器、桌面操作集成。
Coordinate groups of AI agents in the cloud with Flow Nexus. Assign research or development tasks, automate workflows triggered by events or schedules, and monitor execution, queues, and agent capacity through the platform's tools.
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Build Python applications that keep other tasks moving while waiting for network, database, or file operations. Guides the choice of asyncio patterns, with timeouts, cancellation, error handling, and testing for asynchronous code.
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Trace queued jobs from submission to their eventual effects in a CTF sandbox. Compare request-time and worker-time settings, follow retries and failed-message handling, and document the smallest sequence that explains a worker-specific result.
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Create shareable links that open specific Arize resources, including traces, datasets, and evaluators. Use IDs from logs or exported data, with suitable time ranges, to direct teammates to the relevant view.
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Investigate SGLang serving failures by collecting server state, preserving failing requests, and replaying them on a clean target. Summarize evidence and likely causes, then choose the next debugging tool for crashes, stalls, or performance regressions.
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